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Control System
Stability: Routh Criterion
Nilesh Bhaskarrao Bahadure
Ph.D, ME, BE
nbahadure@gmail.com
https://www.sites.google.com/site/nileshbbahadure/home
June 29, 2021
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Overview I
1 Introduction
2 Types of Stable System
3 Routh-Hurwitz Stability Criterion
Disadvantages of Hurwitz Criterion
Techniques of Routh-Hurwitz criterion
4 Examples
5 Special Cases of Routh Array
6 Advantages and Disadvantages of Routh-Hurwitz Stability Criterion
7 Thank You
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The Stability of Linear Feedback Systems
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The Stability of Linear Feedback Systems
The issue of ensuring the stability of a closed-loop feedback system is
central to control system design. Knowing that an unstable closed-loop
system is generally of no practical value, we seek methods to help us
analyze and design stable systems. A stable system should exhibit a
bounded output if the corresponding input is bounded.
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The Stability of Linear Feedback Systems...
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The Stability of Linear Feedback Systems...
The stability of a control system is defined as the ability of any system to
provide a bounded output when a bounded input is applied to it. More
specifically, we can say, that stability allows the system to reach the
steady-state and remain in that state for that particular input even after
variation in the parameters of the system.
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The Stability of Linear Feedback Systems...
The stability of a control system is defined as the ability of any system to
provide a bounded output when a bounded input is applied to it. More
specifically, we can say, that stability allows the system to reach the
steady-state and remain in that state for that particular input even after
variation in the parameters of the system.
Stability is considered to be an important property of a control system. It
is also referred as the systems ability to reach the steady-state.
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Stability of Control System
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Stability of Control System
We have already discussed that a stable system generates bounded output
for bounded input (BIBO).
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Stability of Control System
We have already discussed that a stable system generates bounded output
for bounded input (BIBO).
Now the question arises what is bounded signal?
Bounded value of a signal represents a finite value. More specifically, we
can say, the bounded signal holds a finite value of maxima and minima.
Thus, if maxima and minima of any signal are finite then this means all
the other values between maxima and minima will also be finite.
Suppose we have a signal shown below:
Figure : Bounded signal
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Stability of Control System...
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Stability of Control System...
As we can see that here the maxima and minima of the signal represented
above is having finite values. Thus such a signal is said to be bounded and
if such an output is provided by a system then it is said to be a stable
system.
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Stability of Control System...
As we can see that here the maxima and minima of the signal represented
above is having finite values. Thus such a signal is said to be bounded and
if such an output is provided by a system then it is said to be a stable
system.
Therefore, conversely, we can say that an unstable system provides an
unbounded output when the applied input is bounded in nature.
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Stability of Control System...
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Stability of Control System...
Now, what are unbounded signals?
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Stability of Control System...
Now, what are unbounded signals?
So, generally, the signals whose graph shows continuous rise thereby
showing infinite value such as ramp signal are known as unbounded
signals. The figure shown below represents the unbounded signal:
Figure : Unbounded signal
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Stability of Control System...
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Stability of Control System...
Sometimes we come across asymptotically stable systems which are
defined as the systems whose output progresses 0, when the input is not
present, even when the parameters of the system show variation.
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Stability of Control System...
Sometimes we come across asymptotically stable systems which are
defined as the systems whose output progresses 0, when the input is not
present, even when the parameters of the system show variation.
It is to be noted here that poles of the transfer function, is a factor
defining the stability of the control system.
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How poles can give information regarding the stability of
the system?
Case I
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How poles can give information regarding the stability of
the system?
Case I
When the poles of the transfer function of the system are located on the
left side of the s-plane then it is said to be a stable system. However, as
the poles progress towards 0 or origin, then, in this case, the stability of
the system decreases.
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How poles can give information regarding the stability of
the system?
Case I
When the poles of the transfer function of the system are located on the
left side of the s-plane then it is said to be a stable system. However, as
the poles progress towards 0 or origin, then, in this case, the stability of
the system decreases.
Figure : Poles on left side of the s-plane
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How poles...
Case II
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How poles...
Case II
If for a system, the poles are present in the imaginary axis and are
non-repetitive in nature, then it is said to be a marginally stable system.
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How poles...
Case II
If for a system, the poles are present in the imaginary axis and are
non-repetitive in nature, then it is said to be a marginally stable system.
Figure : Poles on imaginary axis s-plane
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How poles...
Case III
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How poles...
Case III
However, if there exist repetitive poles in the imaginary axis of the s-plane.
Then it is called to be an unstable system.
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How poles...
Case III
However, if there exist repetitive poles in the imaginary axis of the s-plane.
Then it is called to be an unstable system.
Figure : Poles on imaginary axis s-plane
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How poles...
Case IV
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How poles...
Case IV
If a system having poles in the right domain of the s-plane, then such a
system is called an unstable system. The presence of even a single pole in
the right half makes the system unstable.
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How poles...
Case IV
If a system having poles in the right domain of the s-plane, then such a
system is called an unstable system. The presence of even a single pole in
the right half makes the system unstable.
Figure : Poles on right hand side of s-plane
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Absolutely stable system
Absolutely stable system
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Absolutely stable system
Absolutely stable system
An absolutely stable system is the one that provides bounded output even
for the variation in the parameters of the system. This means it is such a
system whose output after reaching a steady-state does not show changes
irrespective of the disturbances or variation in the system parameter values.
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Absolutely stable system
Absolutely stable system
An absolutely stable system is the one that provides bounded output even
for the variation in the parameters of the system. This means it is such a
system whose output after reaching a steady-state does not show changes
irrespective of the disturbances or variation in the system parameter values.
The figure shown below represents the step response of an absolutely
stable system:
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Absolutely stable system
Absolutely stable system
An absolutely stable system is the one that provides bounded output even
for the variation in the parameters of the system. This means it is such a
system whose output after reaching a steady-state does not show changes
irrespective of the disturbances or variation in the system parameter values.
The figure shown below represents the step response of an absolutely
stable system:
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Absolutely stable system...
Absolutely stable system...
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Absolutely stable system...
Absolutely stable system...
The nature of poles for the absolutely stable condition must be real and
negative.
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Absolutely stable system...
Absolutely stable system...
The nature of poles for the absolutely stable condition must be real and
negative.
The figure below represents an unstable system:
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Absolutely stable system...
Absolutely stable system...
The nature of poles for the absolutely stable condition must be real and
negative.
The figure below represents an unstable system:
Figure : Unstable system
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Conditionally stable system
Conditionally stable system
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Conditionally stable system
Conditionally stable system
A conditionally stable system gives bounded output for the only specific
conditions of the system that is defined by the parameter of the system.
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Conditionally stable system
Conditionally stable system
A conditionally stable system gives bounded output for the only specific
conditions of the system that is defined by the parameter of the system.
Thus we can say here the system exhibits stability only under particular
conditions.
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Conditionally stable system
Conditionally stable system
A conditionally stable system gives bounded output for the only specific
conditions of the system that is defined by the parameter of the system.
Thus we can say here the system exhibits stability only under particular
conditions.
And if that particular condition is violated then the system generates
unbounded output.
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Marginally/ Critically stable system
Marginally/ Critically stable system
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Marginally/ Critically stable system
Marginally/ Critically stable system
A marginally stable system is the one that generates a signal which is
oscillating with constant frequency and amplitude when a bounded input is
provided to it.
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Marginally/ Critically stable system
Marginally/ Critically stable system
A marginally stable system is the one that generates a signal which is
oscillating with constant frequency and amplitude when a bounded input is
provided to it.
These oscillations are known as sustained oscillations. The figure here
represents the step response of a marginally stable system:
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Marginally/ Critically stable system
Marginally/ Critically stable system
A marginally stable system is the one that generates a signal which is
oscillating with constant frequency and amplitude when a bounded input is
provided to it.
These oscillations are known as sustained oscillations. The figure here
represents the step response of a marginally stable system:
Figure : Marginally/ Critically stable system 47 / 261
Marginally/ Critically stable system
Marginally/ Critically stable system
A marginally stable system is the one that generates a signal which is
oscillating with constant frequency and amplitude when a bounded input is
provided to it.
These oscillations are known as sustained oscillations. The figure here
represents the step response of a marginally stable system:
Figure : Marginally/ Critically stable system 48 / 261
Marginally/ Critically stable system
Marginally/ Critically stable system
A marginally stable system is the one that generates a signal which is
oscillating with constant frequency and amplitude when a bounded input is
provided to it.
These oscillations are known as sustained oscillations. The figure here
represents the step response of a marginally stable system:
Figure : Marginally/ Critically stable system 49 / 261
Marginally/ Critically stable system...
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Marginally/ Critically stable system...
The nature of the closed-loop poles must be non-repetitive and located on
the imaginary axis.
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Marginally/ Critically stable system...
The nature of the closed-loop poles must be non-repetitive and located on
the imaginary axis.
In this way, the stability of the control system is studied.
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Routh-Hurwitz Stability Criterion
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Routh-Hurwitz Stability Criterion
Routh-Hurwitz stability criterion is an analytical method used for the
determination of stability of a linear time-invariant system. The basis of
this criterion revolves around simply determining the location of poles of
the characteristic equation in either left half or right half of s-plane despite
solving the equation.
54 / 261
Routh-Hurwitz Stability Criterion
Routh-Hurwitz stability criterion is an analytical method used for the
determination of stability of a linear time-invariant system. The basis of
this criterion revolves around simply determining the location of poles of
the characteristic equation in either left half or right half of s-plane despite
solving the equation.
The stability of a control system basically defines its ability to reach the
steady-state and remain there till the time, specific input is maintained
despite the variation in the other factors associated with the system.
55 / 261
Routh-Hurwitz Stability Criterion
Routh-Hurwitz stability criterion is an analytical method used for the
determination of stability of a linear time-invariant system. The basis of
this criterion revolves around simply determining the location of poles of
the characteristic equation in either left half or right half of s-plane despite
solving the equation.
The stability of a control system basically defines its ability to reach the
steady-state and remain there till the time, specific input is maintained
despite the variation in the other factors associated with the system.
Thus, to check whether the system is stable or not, the conditions of
stability criterion must be satisfied.
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Routh-Hurwitz Criterion
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Routh-Hurwitz Criterion
This stability criterion is known to be an algebraic technique that uses the
characteristic equation of the transfer function of the closed-loop control
system in order to determine its stability.
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Routh-Hurwitz Criterion
This stability criterion is known to be an algebraic technique that uses the
characteristic equation of the transfer function of the closed-loop control
system in order to determine its stability.
According to this criterion, there is a necessary condition and a sufficient
condition.
59 / 261
Routh-Hurwitz Criterion
This stability criterion is known to be an algebraic technique that uses the
characteristic equation of the transfer function of the closed-loop control
system in order to determine its stability.
According to this criterion, there is a necessary condition and a sufficient
condition.
If the necessary condition is not satisfied by the system, then it is said to
be an unstable system. However, even after satisfying the necessary
condition, the system may or may not be stable.
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Routh-Hurwitz Criterion
This stability criterion is known to be an algebraic technique that uses the
characteristic equation of the transfer function of the closed-loop control
system in order to determine its stability.
According to this criterion, there is a necessary condition and a sufficient
condition.
If the necessary condition is not satisfied by the system, then it is said to
be an unstable system. However, even after satisfying the necessary
condition, the system may or may not be stable.
Therefore, we need sufficient condition to determine whether the system is
stable or not.
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Routh-Hurwitz Criterion...
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Routh-Hurwitz Criterion...
Suppose the transfer function of the closed-loop system is given as:
C(s)
R(s)
=
b0sm + b1sm−1 + − − − + bm
a0sn + a1sn−1 + − − − + an
=
B(s)
F(s)
where a and b are the two constants here.
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Routh-Hurwitz Criterion...
Suppose the transfer function of the closed-loop system is given as:
C(s)
R(s)
=
b0sm + b1sm−1 + − − − + bm
a0sn + a1sn−1 + − − − + an
=
B(s)
F(s)
where a and b are the two constants here.
On equating F(s) = 0, we will get the closed-loop poles of the system,
which is known as the characteristic equation of the system, given as:
F(s) = a0sn
+ a1sn−1
+ a2sn−2
+ − − − + an
= 0
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Routh-Hurwitz Criterion...
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Routh-Hurwitz Criterion...
Moreover, the roots of this characteristic equation are the poles of the
system with the help of which the stability of the system is decided.
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Routh-Hurwitz Criterion...
Moreover, the roots of this characteristic equation are the poles of the
system with the help of which the stability of the system is decided.
It is to be noted here that before checking the stability of the system using
the Routh-Hurwitz criterion, a basic analysis must be done.
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Routh-Hurwitz Criterion...
Moreover, the roots of this characteristic equation are the poles of the
system with the help of which the stability of the system is decided.
It is to be noted here that before checking the stability of the system using
the Routh-Hurwitz criterion, a basic analysis must be done.
This general test is simply done by analyzing the characteristic equation,
here all the roots of the equation must be present on the left side of the
s-plane.
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Routh-Hurwitz Criterion...
The necessary conditions are discussed below:
1 The coefficients of all the polynomials of the equation should be of a
similar sign.
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Routh-Hurwitz Criterion...
The necessary conditions are discussed below:
1 The coefficients of all the polynomials of the equation should be of a
similar sign.
2 Also, all the coefficients must be present, this means that any of the
power of ’s’ from ’n’ to 0 must not be absent.
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Routh-Hurwitz Criterion...
The necessary conditions are discussed below:
1 The coefficients of all the polynomials of the equation should be of a
similar sign.
2 Also, all the coefficients must be present, this means that any of the
power of ’s’ from ’n’ to 0 must not be absent.
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Routh-Hurwitz Criterion...
The necessary conditions are discussed below:
1 The coefficients of all the polynomials of the equation should be of a
similar sign.
2 Also, all the coefficients must be present, this means that any of the
power of ’s’ from ’n’ to 0 must not be absent.
These two are not sufficient conditions to prove the stability of the system.
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Routh-Hurwitz Criterion...
The necessary conditions are discussed below:
1 The coefficients of all the polynomials of the equation should be of a
similar sign.
2 Also, all the coefficients must be present, this means that any of the
power of ’s’ from ’n’ to 0 must not be absent.
These two are not sufficient conditions to prove the stability of the system.
Initially, the sufficient condition to have the poles in the left half of s-plane
was proposed by Hurwitz. It was known as Hurwitz criterion and states
that all the subdeterminants of the Hurwitz’s determinant must be
positive.
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Disadvantages of Hurwitz Criterion
Disadvantages:
1 Solving the determinants of the higher-order system is quite difficult
and time-consuming.
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Disadvantages of Hurwitz Criterion
Disadvantages:
1 Solving the determinants of the higher-order system is quite difficult
and time-consuming.
2 In the case of an unstable system, the number of roots in the right
half of s-plane is non-determinable by this method.
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Disadvantages of Hurwitz Criterion
Disadvantages:
1 Solving the determinants of the higher-order system is quite difficult
and time-consuming.
2 In the case of an unstable system, the number of roots in the right
half of s-plane is non-determinable by this method.
3 The prediction of marginal stability is not easy.
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Disadvantages of Hurwitz Criterion
Disadvantages:
1 Solving the determinants of the higher-order system is quite difficult
and time-consuming.
2 In the case of an unstable system, the number of roots in the right
half of s-plane is non-determinable by this method.
3 The prediction of marginal stability is not easy.
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Disadvantages of Hurwitz Criterion
Disadvantages:
1 Solving the determinants of the higher-order system is quite difficult
and time-consuming.
2 In the case of an unstable system, the number of roots in the right
half of s-plane is non-determinable by this method.
3 The prediction of marginal stability is not easy.
So, because of these disadvantages, Routh proposed another technique for
determining the stability of the system, this method is generally known as
the Routh-Hurwitz criterion or Routh’s criterion.
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Techniques of Routh-Hurwitz criterion
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Techniques of Routh-Hurwitz criterion
According to Routh, for a stable system the necessary and sufficient
condition is that in a routh array, all the terms that are present in the first
column must be of the similar sign. This means no change of sign (either
from positive to negative or negative to positive) must exist in the first
column of the array.
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Techniques of Routh-Hurwitz criterion
According to Routh, for a stable system the necessary and sufficient
condition is that in a routh array, all the terms that are present in the first
column must be of the similar sign. This means no change of sign (either
from positive to negative or negative to positive) must exist in the first
column of the array.
Therefore, in case if there is any sign change then such a system becomes
unstable.
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Techniques of Routh-Hurwitz criterion
According to Routh, for a stable system the necessary and sufficient
condition is that in a routh array, all the terms that are present in the first
column must be of the similar sign. This means no change of sign (either
from positive to negative or negative to positive) must exist in the first
column of the array.
Therefore, in case if there is any sign change then such a system becomes
unstable.
This is said on the basis that the overall sign changes in the first column
signify the total number of roots lying on the right half of the s-plane,
thereby making the system unstable.
82 / 261
Techniques of Routh-Hurwitz criterion
According to Routh, for a stable system the necessary and sufficient
condition is that in a routh array, all the terms that are present in the first
column must be of the similar sign. This means no change of sign (either
from positive to negative or negative to positive) must exist in the first
column of the array.
Therefore, in case if there is any sign change then such a system becomes
unstable.
This is said on the basis that the overall sign changes in the first column
signify the total number of roots lying on the right half of the s-plane,
thereby making the system unstable.
Thus, in simple words, we can say, that for a system to be stable, each
coefficient of the first column of the array must have a positive sign. If it
is not so, then it is an unstable system. And the number of sign change
that makes the system unstable shows the number of poles that are
present on the right side of the s-plane.
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Techniques of Routh-Hurwitz criterion
According to Routh, for a stable system the necessary and sufficient
condition is that in a routh array, all the terms that are present in the first
column must be of the similar sign. This means no change of sign (either
from positive to negative or negative to positive) must exist in the first
column of the array.
Therefore, in case if there is any sign change then such a system becomes
unstable.
This is said on the basis that the overall sign changes in the first column
signify the total number of roots lying on the right half of the s-plane,
thereby making the system unstable.
Thus, in simple words, we can say, that for a system to be stable, each
coefficient of the first column of the array must have a positive sign. If it
is not so, then it is an unstable system. And the number of sign change
that makes the system unstable shows the number of poles that are
present on the right side of the s-plane.
This is known as the Routh-Hurwitz Criterion.
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What is Routh Array?
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What is Routh Array?
Basically, under the Routh-Hurwitz stability criterion, Routh proposed a
technique by which the coefficients of the characteristic equation are
arranged in a specific manner. This arrangement of the coefficients forms
an array which is known as routh array.
86 / 261
What is Routh Array?
Basically, under the Routh-Hurwitz stability criterion, Routh proposed a
technique by which the coefficients of the characteristic equation are
arranged in a specific manner. This arrangement of the coefficients forms
an array which is known as routh array.
Let us now see how a routh array is formed. Consider the general
characteristic equation:
F(s) = a0sn
+ a1sn−1
+ a2sn−2
+ − − − + an
= 0
87 / 261
What is Routh Array?
Basically, under the Routh-Hurwitz stability criterion, Routh proposed a
technique by which the coefficients of the characteristic equation are
arranged in a specific manner. This arrangement of the coefficients forms
an array which is known as routh array.
Let us now see how a routh array is formed. Consider the general
characteristic equation:
F(s) = a0sn
+ a1sn−1
+ a2sn−2
+ − − − + an
= 0
For the routh array, the first two rows are written from the characteristic
equation directly while the rest of the rows are formed with the help of
previous rows.
88 / 261
What is Routh Array?
Basically, under the Routh-Hurwitz stability criterion, Routh proposed a
technique by which the coefficients of the characteristic equation are
arranged in a specific manner. This arrangement of the coefficients forms
an array which is known as routh array.
Let us now see how a routh array is formed. Consider the general
characteristic equation:
F(s) = a0sn
+ a1sn−1
+ a2sn−2
+ − − − + an
= 0
For the routh array, the first two rows are written from the characteristic
equation directly while the rest of the rows are formed with the help of
previous rows.
It is to be noted here that if in the characteristic equation, n is odd
then the first row of the array will hold the odd coefficients. While if
n is even then there will be even coefficients present in the first row.
89 / 261
What is Routh Array?
Basically, under the Routh-Hurwitz stability criterion, Routh proposed a
technique by which the coefficients of the characteristic equation are
arranged in a specific manner. This arrangement of the coefficients forms
an array which is known as routh array.
Let us now see how a routh array is formed. Consider the general
characteristic equation:
F(s) = a0sn
+ a1sn−1
+ a2sn−2
+ − − − + an
= 0
For the routh array, the first two rows are written from the characteristic
equation directly while the rest of the rows are formed with the help of
previous rows.
It is to be noted here that if in the characteristic equation, n is odd
then the first row of the array will hold the odd coefficients. While if
n is even then there will be even coefficients present in the first row.
In this way, the first and second row of the array will get formed. Let us
now see how the rest of the rows will get formed.
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What is Routh Array?...
91 / 261
What is Routh Array?...
Figure : Routh Array
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What is Routh Array?...
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What is Routh Array?...
So, the third row will be formed using the first and second rows. Let us
see how
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What is Routh Array?...
So, the third row will be formed using the first and second rows. Let us
see how
b1 =
a1a2 − a0a3
a1
,
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What is Routh Array?...
So, the third row will be formed using the first and second rows. Let us
see how
b1 =
a1a2 − a0a3
a1
, b2 =
a1a4 − a0a5
a1
,
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What is Routh Array?...
So, the third row will be formed using the first and second rows. Let us
see how
b1 =
a1a2 − a0a3
a1
, b2 =
a1a4 − a0a5
a1
, b3 =
a1a6 − a0a7
a1
− −−
In a similar way after forming the 3rd row, we can use 2nd and 3rd row to
form the 4th row
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What is Routh Array?...
So, the third row will be formed using the first and second rows. Let us
see how
b1 =
a1a2 − a0a3
a1
, b2 =
a1a4 − a0a5
a1
, b3 =
a1a6 − a0a7
a1
− −−
In a similar way after forming the 3rd row, we can use 2nd and 3rd row to
form the 4th row
c1 =
b1a3 − a1b2
b1
,
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What is Routh Array?...
So, the third row will be formed using the first and second rows. Let us
see how
b1 =
a1a2 − a0a3
a1
, b2 =
a1a4 − a0a5
a1
, b3 =
a1a6 − a0a7
a1
− −−
In a similar way after forming the 3rd row, we can use 2nd and 3rd row to
form the 4th row
c1 =
b1a3 − a1b2
b1
, c2 =
b1a5 − a1b3
b1
,
99 / 261
What is Routh Array?...
So, the third row will be formed using the first and second rows. Let us
see how
b1 =
a1a2 − a0a3
a1
, b2 =
a1a4 − a0a5
a1
, b3 =
a1a6 − a0a7
a1
− −−
In a similar way after forming the 3rd row, we can use 2nd and 3rd row to
form the 4th row
c1 =
b1a3 − a1b2
b1
, c2 =
b1a5 − a1b3
b1
, c3 =
b1a6 − a1b4
b1
− −−
and so on.
100 / 261
What is Routh Array?...
So, the third row will be formed using the first and second rows. Let us
see how
b1 =
a1a2 − a0a3
a1
, b2 =
a1a4 − a0a5
a1
, b3 =
a1a6 − a0a7
a1
− −−
In a similar way after forming the 3rd row, we can use 2nd and 3rd row to
form the 4th row
c1 =
b1a3 − a1b2
b1
, c2 =
b1a5 − a1b3
b1
, c3 =
b1a6 − a1b4
b1
− −−
and so on.
Therefore, we have to continue the process until the time we get the
coefficients for s0, which is nothing but an. In this way, we get routh array
from which the stability of the system is predicted.
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What is Routh Array?...
So, the third row will be formed using the first and second rows. Let us
see how
b1 =
a1a2 − a0a3
a1
, b2 =
a1a4 − a0a5
a1
, b3 =
a1a6 − a0a7
a1
− −−
In a similar way after forming the 3rd row, we can use 2nd and 3rd row to
form the 4th row
c1 =
b1a3 − a1b2
b1
, c2 =
b1a5 − a1b3
b1
, c3 =
b1a6 − a1b4
b1
− −−
and so on.
Therefore, we have to continue the process until the time we get the
coefficients for s0, which is nothing but an. In this way, we get routh array
from which the stability of the system is predicted.
Now there are two special cases that cause the failure of the Routh’s test:
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Two special cases that cause the failure of the Routh’s test
Case 1:
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Two special cases that cause the failure of the Routh’s test
Case 1:
If in any of the rows the first element is 0 and in the same row even a
single non zero element is there then in the next row there will be an
infinite term and this will lead to failure of Routh’s test.
Case 2:
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Two special cases that cause the failure of the Routh’s test
Case 1:
If in any of the rows the first element is 0 and in the same row even a
single non zero element is there then in the next row there will be an
infinite term and this will lead to failure of Routh’s test.
Case 2:
If there is such a row in routh array whose all the elements are 0 then it
will be impossible to determine the next row and thus the Routh’s test
fails in this condition also. This is so because the presence of only 0 in a
row shows the absence of coefficients in that particular row.
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Example: 01
Example
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Example: 01
Example
find the stability of the control system having characteristic equation,
s4
+ 3s3
+ 3s2
+ 2s + 1 = 0
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Example: 01
Solution
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Example: 01
Solution
Step 1: Verify the necessary condition for the Routh-Hurwitz stability.
All the coefficients of the characteristic polynomial, s4 + 3s3 + 3s2 + 2s + 1
are positive. So, the control system satisfies the necessary condition.
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Example: 01
Solution
Step 1: Verify the necessary condition for the Routh-Hurwitz stability.
All the coefficients of the characteristic polynomial, s4 + 3s3 + 3s2 + 2s + 1
are positive. So, the control system satisfies the necessary condition.
Step 2: Form the Routh array for the given characteristic polynomial.
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Example: 01
Solution
Step 1: Verify the necessary condition for the Routh-Hurwitz stability.
All the coefficients of the characteristic polynomial, s4 + 3s3 + 3s2 + 2s + 1
are positive. So, the control system satisfies the necessary condition.
Step 2: Form the Routh array for the given characteristic polynomial.
s4 1 3 1
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Example: 01
Solution
Step 1: Verify the necessary condition for the Routh-Hurwitz stability.
All the coefficients of the characteristic polynomial, s4 + 3s3 + 3s2 + 2s + 1
are positive. So, the control system satisfies the necessary condition.
Step 2: Form the Routh array for the given characteristic polynomial.
s4 1 3 1
s3 3 2
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Example: 01
Solution
Step 1: Verify the necessary condition for the Routh-Hurwitz stability.
All the coefficients of the characteristic polynomial, s4 + 3s3 + 3s2 + 2s + 1
are positive. So, the control system satisfies the necessary condition.
Step 2: Form the Routh array for the given characteristic polynomial.
s4 1 3 1
s3 3 2
s2 (3∗3)−(2∗1)
3 = 7
3
(3∗1)−(0∗1)
3 = 1
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Example: 01
Solution
Step 1: Verify the necessary condition for the Routh-Hurwitz stability.
All the coefficients of the characteristic polynomial, s4 + 3s3 + 3s2 + 2s + 1
are positive. So, the control system satisfies the necessary condition.
Step 2: Form the Routh array for the given characteristic polynomial.
s4 1 3 1
s3 3 2
s2 (3∗3)−(2∗1)
3 = 7
3
(3∗1)−(0∗1)
3 = 1
s1 ( 7
3
∗2)−(1∗3)
7
3
= 5
7
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Example: 01
Solution
Step 1: Verify the necessary condition for the Routh-Hurwitz stability.
All the coefficients of the characteristic polynomial, s4 + 3s3 + 3s2 + 2s + 1
are positive. So, the control system satisfies the necessary condition.
Step 2: Form the Routh array for the given characteristic polynomial.
s4 1 3 1
s3 3 2
s2 (3∗3)−(2∗1)
3 = 7
3
(3∗1)−(0∗1)
3 = 1
s1 ( 7
3
∗2)−(1∗3)
7
3
= 5
7
s0 1
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Example: 01
Solution
Step 1: Verify the necessary condition for the Routh-Hurwitz stability.
All the coefficients of the characteristic polynomial, s4 + 3s3 + 3s2 + 2s + 1
are positive. So, the control system satisfies the necessary condition.
Step 2: Form the Routh array for the given characteristic polynomial.
s4 1 3 1
s3 3 2
s2 (3∗3)−(2∗1)
3 = 7
3
(3∗1)−(0∗1)
3 = 1
s1 ( 7
3
∗2)−(1∗3)
7
3
= 5
7
s0 1
Step 3: Verify the sufficient condition for the Routh-Hurwitz stability.
All the elements of the first column of the Routh array are
positive. There is no sign change in the first column of
the Routh array. So, the control system is stable.
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Example: 02
Example
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Example: 02
Example
Check the stability of the system whose characteristic equation is given by
s4
+ 2s3
+ 6s2
+ 4s + 1 = 0
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Example: 02
Solution
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Example: 02
Solution
Step 1: Verify the necessary condition for the Routh-Hurwitz stability.
All the coefficients of the characteristic polynomial,
s4 + 2s3 + 6s2 + 4s + 1 = 0 are positive. So, the control system satisfies
the necessary condition.
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Example: 02
Solution
Step 1: Verify the necessary condition for the Routh-Hurwitz stability.
All the coefficients of the characteristic polynomial,
s4 + 2s3 + 6s2 + 4s + 1 = 0 are positive. So, the control system satisfies
the necessary condition.
Step 2: Form the Routh array for the given characteristic polynomial.
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Example: 02
Solution
Step 1: Verify the necessary condition for the Routh-Hurwitz stability.
All the coefficients of the characteristic polynomial,
s4 + 2s3 + 6s2 + 4s + 1 = 0 are positive. So, the control system satisfies
the necessary condition.
Step 2: Form the Routh array for the given characteristic polynomial.
s4 1 6 1
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Example: 02
Solution
Step 1: Verify the necessary condition for the Routh-Hurwitz stability.
All the coefficients of the characteristic polynomial,
s4 + 2s3 + 6s2 + 4s + 1 = 0 are positive. So, the control system satisfies
the necessary condition.
Step 2: Form the Routh array for the given characteristic polynomial.
s4 1 6 1
s3 2 4
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Example: 02
Solution
Step 1: Verify the necessary condition for the Routh-Hurwitz stability.
All the coefficients of the characteristic polynomial,
s4 + 2s3 + 6s2 + 4s + 1 = 0 are positive. So, the control system satisfies
the necessary condition.
Step 2: Form the Routh array for the given characteristic polynomial.
s4 1 6 1
s3 2 4
s2 (2∗6)−(4∗1)
2 = 4 (2∗1)−(0∗1)
2 = 1
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Example: 02
Solution
Step 1: Verify the necessary condition for the Routh-Hurwitz stability.
All the coefficients of the characteristic polynomial,
s4 + 2s3 + 6s2 + 4s + 1 = 0 are positive. So, the control system satisfies
the necessary condition.
Step 2: Form the Routh array for the given characteristic polynomial.
s4 1 6 1
s3 2 4
s2 (2∗6)−(4∗1)
2 = 4 (2∗1)−(0∗1)
2 = 1
s1 (4∗4)−(1∗2)
4 = 3.5
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Example: 02
Solution
Step 1: Verify the necessary condition for the Routh-Hurwitz stability.
All the coefficients of the characteristic polynomial,
s4 + 2s3 + 6s2 + 4s + 1 = 0 are positive. So, the control system satisfies
the necessary condition.
Step 2: Form the Routh array for the given characteristic polynomial.
s4 1 6 1
s3 2 4
s2 (2∗6)−(4∗1)
2 = 4 (2∗1)−(0∗1)
2 = 1
s1 (4∗4)−(1∗2)
4 = 3.5
s0 1
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Example: 02
Solution
Step 1: Verify the necessary condition for the Routh-Hurwitz stability.
All the coefficients of the characteristic polynomial,
s4 + 2s3 + 6s2 + 4s + 1 = 0 are positive. So, the control system satisfies
the necessary condition.
Step 2: Form the Routh array for the given characteristic polynomial.
s4 1 6 1
s3 2 4
s2 (2∗6)−(4∗1)
2 = 4 (2∗1)−(0∗1)
2 = 1
s1 (4∗4)−(1∗2)
4 = 3.5
s0 1
Step 3: Verify the sufficient condition for the Routh-Hurwitz stability.
Since all the coefficients in the first column are of the
same sign, i.e., positive, the given equation has no roots
with positive real parts; therefore, the system is said to
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Example: 03
Example
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Example: 03
Example
Find stability of the following system given by G(s) = K
s(s+1) and H(s) = 1
using Routh-Hurwitz stability criterion.
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Example: 03
Solution
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Example: 03
Solution
In the system T(s) = G(s)
1+G(s)H(s) =
K
s(s+1)
1+ K
s(s+1)
Characteristics equation
B(s) = s2
+ s + K = 0
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Example: 03
Solution
In the system T(s) = G(s)
1+G(s)H(s) =
K
s(s+1)
1+ K
s(s+1)
Characteristics equation
B(s) = s2
+ s + K = 0
Step 1: Verify the necessary condition for the Routh-Hurwitz stability.
All the coefficients of the characteristic polynomial,
B(s) = s2 + s + K = 0 are positive. So, the control system satisfies the
necessary condition (Assuming K > 0).
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Example: 03
Solution
In the system T(s) = G(s)
1+G(s)H(s) =
K
s(s+1)
1+ K
s(s+1)
Characteristics equation
B(s) = s2
+ s + K = 0
Step 1: Verify the necessary condition for the Routh-Hurwitz stability.
All the coefficients of the characteristic polynomial,
B(s) = s2 + s + K = 0 are positive. So, the control system satisfies the
necessary condition (Assuming K > 0).
Step 2: Form the Routh array for the given characteristic polynomial.
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Example: 03
Solution
In the system T(s) = G(s)
1+G(s)H(s) =
K
s(s+1)
1+ K
s(s+1)
Characteristics equation
B(s) = s2
+ s + K = 0
Step 1: Verify the necessary condition for the Routh-Hurwitz stability.
All the coefficients of the characteristic polynomial,
B(s) = s2 + s + K = 0 are positive. So, the control system satisfies the
necessary condition (Assuming K > 0).
Step 2: Form the Routh array for the given characteristic polynomial.
s2 1 K
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Example: 03
Solution
In the system T(s) = G(s)
1+G(s)H(s) =
K
s(s+1)
1+ K
s(s+1)
Characteristics equation
B(s) = s2
+ s + K = 0
Step 1: Verify the necessary condition for the Routh-Hurwitz stability.
All the coefficients of the characteristic polynomial,
B(s) = s2 + s + K = 0 are positive. So, the control system satisfies the
necessary condition (Assuming K > 0).
Step 2: Form the Routh array for the given characteristic polynomial.
s2 1 K
s1 1 0
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Example: 03
Solution
In the system T(s) = G(s)
1+G(s)H(s) =
K
s(s+1)
1+ K
s(s+1)
Characteristics equation
B(s) = s2
+ s + K = 0
Step 1: Verify the necessary condition for the Routh-Hurwitz stability.
All the coefficients of the characteristic polynomial,
B(s) = s2 + s + K = 0 are positive. So, the control system satisfies the
necessary condition (Assuming K > 0).
Step 2: Form the Routh array for the given characteristic polynomial.
s2 1 K
s1 1 0
s0 K
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Example: 03...
Solution
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Example: 03...
Solution
Step 3: Verify the sufficient condition for the Routh-Hurwitz stability.
There are no sign changes in first column elements of this
array.Therefore, the system is always stable for K > 0.
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Example: 04
Example
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Example: 04
Example
Find stability of the following system given by G(s) = K
s(s+2)(s+4) and
H(s) = 1 using Routh-Hurwitz stability criterion.
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Example: 04
Solution
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Example: 04
Solution
In the system T(s) = G(s)
1+G(s)H(s) =
K
s(s+2)(s+4)
1+ K
s(s+2)(s+4)
Characteristics equation
B(s) = s3
+ 6s2
+ 8s + K = 0
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Example: 04
Solution
In the system T(s) = G(s)
1+G(s)H(s) =
K
s(s+2)(s+4)
1+ K
s(s+2)(s+4)
Characteristics equation
B(s) = s3
+ 6s2
+ 8s + K = 0
Step 1: Verify the necessary condition for the Routh-Hurwitz stability.
All the coefficients of the characteristic polynomial,
B(s) = s3 + 6s2 + 8s + K = 0 are positive. So, the control system
satisfies the necessary condition (Assuming K > 0).
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Example: 04
Solution
In the system T(s) = G(s)
1+G(s)H(s) =
K
s(s+2)(s+4)
1+ K
s(s+2)(s+4)
Characteristics equation
B(s) = s3
+ 6s2
+ 8s + K = 0
Step 1: Verify the necessary condition for the Routh-Hurwitz stability.
All the coefficients of the characteristic polynomial,
B(s) = s3 + 6s2 + 8s + K = 0 are positive. So, the control system
satisfies the necessary condition (Assuming K > 0).
Step 2: Form the Routh array for the given characteristic polynomial.
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Example: 04
Solution
In the system T(s) = G(s)
1+G(s)H(s) =
K
s(s+2)(s+4)
1+ K
s(s+2)(s+4)
Characteristics equation
B(s) = s3
+ 6s2
+ 8s + K = 0
Step 1: Verify the necessary condition for the Routh-Hurwitz stability.
All the coefficients of the characteristic polynomial,
B(s) = s3 + 6s2 + 8s + K = 0 are positive. So, the control system
satisfies the necessary condition (Assuming K > 0).
Step 2: Form the Routh array for the given characteristic polynomial.
s3 1 8
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Example: 04
Solution
In the system T(s) = G(s)
1+G(s)H(s) =
K
s(s+2)(s+4)
1+ K
s(s+2)(s+4)
Characteristics equation
B(s) = s3
+ 6s2
+ 8s + K = 0
Step 1: Verify the necessary condition for the Routh-Hurwitz stability.
All the coefficients of the characteristic polynomial,
B(s) = s3 + 6s2 + 8s + K = 0 are positive. So, the control system
satisfies the necessary condition (Assuming K > 0).
Step 2: Form the Routh array for the given characteristic polynomial.
s3 1 8
s2 6 K
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Example: 04
Solution
In the system T(s) = G(s)
1+G(s)H(s) =
K
s(s+2)(s+4)
1+ K
s(s+2)(s+4)
Characteristics equation
B(s) = s3
+ 6s2
+ 8s + K = 0
Step 1: Verify the necessary condition for the Routh-Hurwitz stability.
All the coefficients of the characteristic polynomial,
B(s) = s3 + 6s2 + 8s + K = 0 are positive. So, the control system
satisfies the necessary condition (Assuming K > 0).
Step 2: Form the Routh array for the given characteristic polynomial.
s3 1 8
s2 6 K
s1 48−K
6 0
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Example: 04
Solution
In the system T(s) = G(s)
1+G(s)H(s) =
K
s(s+2)(s+4)
1+ K
s(s+2)(s+4)
Characteristics equation
B(s) = s3
+ 6s2
+ 8s + K = 0
Step 1: Verify the necessary condition for the Routh-Hurwitz stability.
All the coefficients of the characteristic polynomial,
B(s) = s3 + 6s2 + 8s + K = 0 are positive. So, the control system
satisfies the necessary condition (Assuming K > 0).
Step 2: Form the Routh array for the given characteristic polynomial.
s3 1 8
s2 6 K
s1 48−K
6 0
s0 K
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Example: 04...
Solution
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Example: 04...
Solution
Step 3: Verify the sufficient condition for the Routh-Hurwitz stability.
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Example: 04...
Solution
Step 3: Verify the sufficient condition for the Routh-Hurwitz stability.
There are no sign changes in first column elements of this
array if K < 48. Therefore, the system is always stable
for 0 < K < 48
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Example: 05
Example
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Example: 05
Example
Find stability of the following system given by B(s) = s3 + 5s2 + 10s + 3
using Routh-Hurwitz stability criterion.
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Example: 05
Solution
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Example: 05
Solution
Step 1: Verify the necessary condition for the Routh-Hurwitz stability.
All the coefficients of the characteristic polynomial,
B(s) = s3 + 5s2 + 10s + 3 = 0 are positive. So, the control system
satisfies the necessary condition.
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Example: 05
Solution
Step 1: Verify the necessary condition for the Routh-Hurwitz stability.
All the coefficients of the characteristic polynomial,
B(s) = s3 + 5s2 + 10s + 3 = 0 are positive. So, the control system
satisfies the necessary condition.
Step 2: Form the Routh array for the given characteristic polynomial.
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Example: 05
Solution
Step 1: Verify the necessary condition for the Routh-Hurwitz stability.
All the coefficients of the characteristic polynomial,
B(s) = s3 + 5s2 + 10s + 3 = 0 are positive. So, the control system
satisfies the necessary condition.
Step 2: Form the Routh array for the given characteristic polynomial.
s3 1 10
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Example: 05
Solution
Step 1: Verify the necessary condition for the Routh-Hurwitz stability.
All the coefficients of the characteristic polynomial,
B(s) = s3 + 5s2 + 10s + 3 = 0 are positive. So, the control system
satisfies the necessary condition.
Step 2: Form the Routh array for the given characteristic polynomial.
s3 1 10
s2 5 3
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Example: 05
Solution
Step 1: Verify the necessary condition for the Routh-Hurwitz stability.
All the coefficients of the characteristic polynomial,
B(s) = s3 + 5s2 + 10s + 3 = 0 are positive. So, the control system
satisfies the necessary condition.
Step 2: Form the Routh array for the given characteristic polynomial.
s3 1 10
s2 5 3
s1 50−3
5 = 9.4 0
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Example: 05
Solution
Step 1: Verify the necessary condition for the Routh-Hurwitz stability.
All the coefficients of the characteristic polynomial,
B(s) = s3 + 5s2 + 10s + 3 = 0 are positive. So, the control system
satisfies the necessary condition.
Step 2: Form the Routh array for the given characteristic polynomial.
s3 1 10
s2 5 3
s1 50−3
5 = 9.4 0
s0 3
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Example: 05...
Solution
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Example: 05...
Solution
Step 3: Verify the sufficient condition for the Routh-Hurwitz stability.
There are no sign changes in first column elements of this
array. Therefore, the system is always stable.
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Do it by yourself
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Example: 06
Example
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Example: 06
Example
Find stability of the following system given by B(s) = s3 + 2s2 + 3s + 10
using Routh-Hurwitz stability criterion.
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Example: 06
Solution
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Example: 06
Solution
Step 1: Verify the necessary condition for the Routh-Hurwitz stability.
All the coefficients of the characteristic polynomial,
B(s) = s3 + 2s2 + 3s + 10 = 0 are positive. So, the control system
satisfies the necessary condition.
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Example: 06
Solution
Step 1: Verify the necessary condition for the Routh-Hurwitz stability.
All the coefficients of the characteristic polynomial,
B(s) = s3 + 2s2 + 3s + 10 = 0 are positive. So, the control system
satisfies the necessary condition.
Step 2: Form the Routh array for the given characteristic polynomial.
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Example: 06
Solution
Step 1: Verify the necessary condition for the Routh-Hurwitz stability.
All the coefficients of the characteristic polynomial,
B(s) = s3 + 2s2 + 3s + 10 = 0 are positive. So, the control system
satisfies the necessary condition.
Step 2: Form the Routh array for the given characteristic polynomial.
s3 1 3
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Example: 06
Solution
Step 1: Verify the necessary condition for the Routh-Hurwitz stability.
All the coefficients of the characteristic polynomial,
B(s) = s3 + 2s2 + 3s + 10 = 0 are positive. So, the control system
satisfies the necessary condition.
Step 2: Form the Routh array for the given characteristic polynomial.
s3 1 3
s2 2 10
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Example: 06
Solution
Step 1: Verify the necessary condition for the Routh-Hurwitz stability.
All the coefficients of the characteristic polynomial,
B(s) = s3 + 2s2 + 3s + 10 = 0 are positive. So, the control system
satisfies the necessary condition.
Step 2: Form the Routh array for the given characteristic polynomial.
s3 1 3
s2 2 10
s1 6−10
2 = −2 0
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Example: 06
Solution
Step 1: Verify the necessary condition for the Routh-Hurwitz stability.
All the coefficients of the characteristic polynomial,
B(s) = s3 + 2s2 + 3s + 10 = 0 are positive. So, the control system
satisfies the necessary condition.
Step 2: Form the Routh array for the given characteristic polynomial.
s3 1 3
s2 2 10
s1 6−10
2 = −2 0
s0 10
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Example: 06...
Solution
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Example: 06...
Solution
Step 3: Verify the sufficient condition for the Routh-Hurwitz stability.
There are two sign changes in first column elements of this
array. Therefore, the system is unstable.
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Special Cases of Routh Array
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Special Cases of Routh Array
We may come across two types of situations, while forming the Routh
table. It is difficult to complete the Routh table from these two situations.
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Special Cases of Routh Array
We may come across two types of situations, while forming the Routh
table. It is difficult to complete the Routh table from these two situations.
The two special cases are:
1 The first element of any row of the Routh array is zero.
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Special Cases of Routh Array
We may come across two types of situations, while forming the Routh
table. It is difficult to complete the Routh table from these two situations.
The two special cases are:
1 The first element of any row of the Routh array is zero.
2 All the elements of any row of the Routh array are zero.
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Case I: First Element of any row of the Routh array is zero
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Case I: First Element of any row of the Routh array is zero
If any row of the Routh array contains only the first element as zero and at
least one of the remaining elements have non-zero value, then replace the
first element with a small positive integer, . And then continue the
process of completing the Routh table. Now, find the number of sign
changes in the first column of the Routh table by substituting  tends to
zero.
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Example: 07
Example
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Example: 07
Example
Find stability of the following system given by
B(s) = s5 + 2s4 + 4s3 + 8s2 + 3s + 1 using Routh-Hurwitz stability
criterion.
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Example: 07
Solution
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Example: 07
Solution
Step 1: Verify the necessary condition for the Routh-Hurwitz stability.
All the coefficients of the characteristic polynomial,
B(s) = s5 + 2s4 + 4s3 + 8s2 + 3s + 1 = 0 are positive. So, the control
system satisfies the necessary condition.
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Example: 07
Solution
Step 1: Verify the necessary condition for the Routh-Hurwitz stability.
All the coefficients of the characteristic polynomial,
B(s) = s5 + 2s4 + 4s3 + 8s2 + 3s + 1 = 0 are positive. So, the control
system satisfies the necessary condition.
Step 2: Form the Routh array for the given characteristic polynomial.
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Example: 07
Solution
Step 1: Verify the necessary condition for the Routh-Hurwitz stability.
All the coefficients of the characteristic polynomial,
B(s) = s5 + 2s4 + 4s3 + 8s2 + 3s + 1 = 0 are positive. So, the control
system satisfies the necessary condition.
Step 2: Form the Routh array for the given characteristic polynomial.
s5 1 4 3
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Example: 07
Solution
Step 1: Verify the necessary condition for the Routh-Hurwitz stability.
All the coefficients of the characteristic polynomial,
B(s) = s5 + 2s4 + 4s3 + 8s2 + 3s + 1 = 0 are positive. So, the control
system satisfies the necessary condition.
Step 2: Form the Routh array for the given characteristic polynomial.
s5 1 4 3
s4 2 8 1
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Example: 07
Solution
Step 1: Verify the necessary condition for the Routh-Hurwitz stability.
All the coefficients of the characteristic polynomial,
B(s) = s5 + 2s4 + 4s3 + 8s2 + 3s + 1 = 0 are positive. So, the control
system satisfies the necessary condition.
Step 2: Form the Routh array for the given characteristic polynomial.
s5 1 4 3
s4 2 8 1
s3 8−8
2 = 0 6−1
2 = 2.5 0
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Example: 07
Solution
Step 1: Verify the necessary condition for the Routh-Hurwitz stability.
All the coefficients of the characteristic polynomial,
B(s) = s5 + 2s4 + 4s3 + 8s2 + 3s + 1 = 0 are positive. So, the control
system satisfies the necessary condition.
Step 2: Form the Routh array for the given characteristic polynomial.
s5 1 4 3
s4 2 8 1
s3 8−8
2 = 0 6−1
2 = 2.5 0
s2 ∞
190 / 261
Example: 07
Solution
Step 1: Verify the necessary condition for the Routh-Hurwitz stability.
All the coefficients of the characteristic polynomial,
B(s) = s5 + 2s4 + 4s3 + 8s2 + 3s + 1 = 0 are positive. So, the control
system satisfies the necessary condition.
Step 2: Form the Routh array for the given characteristic polynomial.
s5 1 4 3
s4 2 8 1
s3 8−8
2 = 0 6−1
2 = 2.5 0
s2 ∞
s1
191 / 261
Example: 07
Solution
Step 1: Verify the necessary condition for the Routh-Hurwitz stability.
All the coefficients of the characteristic polynomial,
B(s) = s5 + 2s4 + 4s3 + 8s2 + 3s + 1 = 0 are positive. So, the control
system satisfies the necessary condition.
Step 2: Form the Routh array for the given characteristic polynomial.
s5 1 4 3
s4 2 8 1
s3 8−8
2 = 0 6−1
2 = 2.5 0
s2 ∞
s1
s0
192 / 261
Example: 07
Solution
Step 1: Verify the necessary condition for the Routh-Hurwitz stability.
All the coefficients of the characteristic polynomial,
B(s) = s5 + 2s4 + 4s3 + 8s2 + 3s + 1 = 0 are positive. So, the control
system satisfies the necessary condition.
Step 2: Form the Routh array for the given characteristic polynomial.
s5 1 4 3
s4 2 8 1
s3 8−8
2 = 0 6−1
2 = 2.5 0
s2 ∞
s1
s0
Here, the criterion fails. To remove the above difficulty, the following two
methods can be used.
193 / 261
Example: 07: Method I
Solution
1 Replace 0 by  (very small number) and complete the array with .
Now, Routh’s array becomes
194 / 261
Example: 07: Method I
Solution
1 Replace 0 by  (very small number) and complete the array with .
2 Examine the sign change by taking  → 0
Now, Routh’s array becomes
195 / 261
Example: 07: Method I
Solution
1 Replace 0 by  (very small number) and complete the array with .
2 Examine the sign change by taking  → 0
Now, Routh’s array becomes
196 / 261
Example: 07: Method I
Solution
1 Replace 0 by  (very small number) and complete the array with .
2 Examine the sign change by taking  → 0
Now, Routh’s array becomes
s5 1 4 3
197 / 261
Example: 07: Method I
Solution
1 Replace 0 by  (very small number) and complete the array with .
2 Examine the sign change by taking  → 0
Now, Routh’s array becomes
s5 1 4 3
s4 2 8 1
198 / 261
Example: 07: Method I
Solution
1 Replace 0 by  (very small number) and complete the array with .
2 Examine the sign change by taking  → 0
Now, Routh’s array becomes
s5 1 4 3
s4 2 8 1
s3  6−1
2 = 2.5 0
199 / 261
Example: 07: Method I
Solution
1 Replace 0 by  (very small number) and complete the array with .
2 Examine the sign change by taking  → 0
Now, Routh’s array becomes
s5 1 4 3
s4 2 8 1
s3  6−1
2 = 2.5 0
s2 5−8
 1 0
200 / 261
Example: 07: Method I
Solution
1 Replace 0 by  (very small number) and complete the array with .
2 Examine the sign change by taking  → 0
Now, Routh’s array becomes
s5 1 4 3
s4 2 8 1
s3  6−1
2 = 2.5 0
s2 5−8
 1 0
s1 2.5(5−8

)−
5−8

201 / 261
Example: 07: Method I
Solution
1 Replace 0 by  (very small number) and complete the array with .
2 Examine the sign change by taking  → 0
Now, Routh’s array becomes
s5 1 4 3
s4 2 8 1
s3  6−1
2 = 2.5 0
s2 5−8
 1 0
s1 2.5(5−8

)−
5−8

s0 1
202 / 261
Example: 07...
Solution
203 / 261
Example: 07...
Solution
Step 3: Verify the sufficient condition for the Routh-Hurwitz stability.
There are two sign changes in first column elements of this
array. Therefore, the system is unstable.
204 / 261
Example: 07: Method II
Solution
205 / 261
Example: 07: Method II
Solution
Replace s by 1
Z
. The system characteristic equation s5
+ 2s4
+ 4s3
+ 8s2
+ 3s + 1 = 0
becomes
1
Z5
+
2
Z4
+
4
Z3
+
8
Z2
+
3
Z
+ 1 = 0
1 + 2Z1
+ 4Z2
+ 8Z3
+ 3Z4
+ Z5
Z5
= 0
Z5
+ 3Z4
+ 8Z3
+ 4Z2
+ 2Z + 1 = 0
Now, the Routh’s array becomes
206 / 261
Example: 07: Method II
Solution
Replace s by 1
Z
. The system characteristic equation s5
+ 2s4
+ 4s3
+ 8s2
+ 3s + 1 = 0
becomes
1
Z5
+
2
Z4
+
4
Z3
+
8
Z2
+
3
Z
+ 1 = 0
1 + 2Z1
+ 4Z2
+ 8Z3
+ 3Z4
+ Z5
Z5
= 0
Z5
+ 3Z4
+ 8Z3
+ 4Z2
+ 2Z + 1 = 0
Now, the Routh’s array becomes
s5
1 8 2
207 / 261
Example: 07: Method II
Solution
Replace s by 1
Z
. The system characteristic equation s5
+ 2s4
+ 4s3
+ 8s2
+ 3s + 1 = 0
becomes
1
Z5
+
2
Z4
+
4
Z3
+
8
Z2
+
3
Z
+ 1 = 0
1 + 2Z1
+ 4Z2
+ 8Z3
+ 3Z4
+ Z5
Z5
= 0
Z5
+ 3Z4
+ 8Z3
+ 4Z2
+ 2Z + 1 = 0
Now, the Routh’s array becomes
s5
1 8 2
s4
3 4 1
208 / 261
Example: 07: Method II
Solution
Replace s by 1
Z
. The system characteristic equation s5
+ 2s4
+ 4s3
+ 8s2
+ 3s + 1 = 0
becomes
1
Z5
+
2
Z4
+
4
Z3
+
8
Z2
+
3
Z
+ 1 = 0
1 + 2Z1
+ 4Z2
+ 8Z3
+ 3Z4
+ Z5
Z5
= 0
Z5
+ 3Z4
+ 8Z3
+ 4Z2
+ 2Z + 1 = 0
Now, the Routh’s array becomes
s5
1 8 2
s4
3 4 1
s3
6.67 1.67 0
209 / 261
Example: 07: Method II
Solution
Replace s by 1
Z
. The system characteristic equation s5
+ 2s4
+ 4s3
+ 8s2
+ 3s + 1 = 0
becomes
1
Z5
+
2
Z4
+
4
Z3
+
8
Z2
+
3
Z
+ 1 = 0
1 + 2Z1
+ 4Z2
+ 8Z3
+ 3Z4
+ Z5
Z5
= 0
Z5
+ 3Z4
+ 8Z3
+ 4Z2
+ 2Z + 1 = 0
Now, the Routh’s array becomes
s5
1 8 2
s4
3 4 1
s3
6.67 1.67 0
s2
3.24 1 0
210 / 261
Example: 07: Method II
Solution
Replace s by 1
Z
. The system characteristic equation s5
+ 2s4
+ 4s3
+ 8s2
+ 3s + 1 = 0
becomes
1
Z5
+
2
Z4
+
4
Z3
+
8
Z2
+
3
Z
+ 1 = 0
1 + 2Z1
+ 4Z2
+ 8Z3
+ 3Z4
+ Z5
Z5
= 0
Z5
+ 3Z4
+ 8Z3
+ 4Z2
+ 2Z + 1 = 0
Now, the Routh’s array becomes
s5
1 8 2
s4
3 4 1
s3
6.67 1.67 0
s2
3.24 1 0
s1
-0.388 0 0
211 / 261
Example: 07: Method II
Solution
Replace s by 1
Z
. The system characteristic equation s5
+ 2s4
+ 4s3
+ 8s2
+ 3s + 1 = 0
becomes
1
Z5
+
2
Z4
+
4
Z3
+
8
Z2
+
3
Z
+ 1 = 0
1 + 2Z1
+ 4Z2
+ 8Z3
+ 3Z4
+ Z5
Z5
= 0
Z5
+ 3Z4
+ 8Z3
+ 4Z2
+ 2Z + 1 = 0
Now, the Routh’s array becomes
s5
1 8 2
s4
3 4 1
s3
6.67 1.67 0
s2
3.24 1 0
s1
-0.388 0 0
s0
1 0 0
There are two sign changes in first column elements of this array.
Therefore, the system is unstable. 212 / 261
Case II: All Elements of any row of the Routh array is zero
213 / 261
Case II: All Elements of any row of the Routh array is zero
If there is such a row in Routh array whose all the elements are 0 then it
will be impossible to determine the next row and thus the Rouths test fails
in this condition also. This is so because the presence of only 0 in a row
shows the absence of coefficients in that particular row.
214 / 261
Example: 08
Example
215 / 261
Example: 08
Example
Find stability of the following system given by
B(s) = s5 + 2s4 + 2s3 + 4s2 + 4s + 8 using Routh-Hurwitz stability
criterion.
216 / 261
Example: 08
Solution
217 / 261
Example: 08
Solution
Step 1: Verify the necessary condition for the Routh-Hurwitz stability.
All the coefficients of the characteristic polynomial,
B(s) = s5 + 2s4 + 2s3 + 4s2 + 4s + 8 = 0 are positive. So, the control
system satisfies the necessary condition.
218 / 261
Example: 08
Solution
Step 1: Verify the necessary condition for the Routh-Hurwitz stability.
All the coefficients of the characteristic polynomial,
B(s) = s5 + 2s4 + 2s3 + 4s2 + 4s + 8 = 0 are positive. So, the control
system satisfies the necessary condition.
Step 2: Form the Routh array for the given characteristic polynomial.
219 / 261
Example: 08
Solution
Step 1: Verify the necessary condition for the Routh-Hurwitz stability.
All the coefficients of the characteristic polynomial,
B(s) = s5 + 2s4 + 2s3 + 4s2 + 4s + 8 = 0 are positive. So, the control
system satisfies the necessary condition.
Step 2: Form the Routh array for the given characteristic polynomial.
s5 1 2 4
220 / 261
Example: 08
Solution
Step 1: Verify the necessary condition for the Routh-Hurwitz stability.
All the coefficients of the characteristic polynomial,
B(s) = s5 + 2s4 + 2s3 + 4s2 + 4s + 8 = 0 are positive. So, the control
system satisfies the necessary condition.
Step 2: Form the Routh array for the given characteristic polynomial.
s5 1 2 4
s4 2 4 8
221 / 261
Example: 08
Solution
Step 1: Verify the necessary condition for the Routh-Hurwitz stability.
All the coefficients of the characteristic polynomial,
B(s) = s5 + 2s4 + 2s3 + 4s2 + 4s + 8 = 0 are positive. So, the control
system satisfies the necessary condition.
Step 2: Form the Routh array for the given characteristic polynomial.
s5 1 2 4
s4 2 4 8
s3 0 0 0
222 / 261
Example: 08
Solution
Step 1: Verify the necessary condition for the Routh-Hurwitz stability.
All the coefficients of the characteristic polynomial,
B(s) = s5 + 2s4 + 2s3 + 4s2 + 4s + 8 = 0 are positive. So, the control
system satisfies the necessary condition.
Step 2: Form the Routh array for the given characteristic polynomial.
s5 1 2 4
s4 2 4 8
s3 0 0 0
s2
223 / 261
Example: 08
Solution
Step 1: Verify the necessary condition for the Routh-Hurwitz stability.
All the coefficients of the characteristic polynomial,
B(s) = s5 + 2s4 + 2s3 + 4s2 + 4s + 8 = 0 are positive. So, the control
system satisfies the necessary condition.
Step 2: Form the Routh array for the given characteristic polynomial.
s5 1 2 4
s4 2 4 8
s3 0 0 0
s2
s1
224 / 261
Example: 08
Solution
Step 1: Verify the necessary condition for the Routh-Hurwitz stability.
All the coefficients of the characteristic polynomial,
B(s) = s5 + 2s4 + 2s3 + 4s2 + 4s + 8 = 0 are positive. So, the control
system satisfies the necessary condition.
Step 2: Form the Routh array for the given characteristic polynomial.
s5 1 2 4
s4 2 4 8
s3 0 0 0
s2
s1
s0
225 / 261
Example: 08
Solution
Step 1: Verify the necessary condition for the Routh-Hurwitz stability.
All the coefficients of the characteristic polynomial,
B(s) = s5 + 2s4 + 2s3 + 4s2 + 4s + 8 = 0 are positive. So, the control
system satisfies the necessary condition.
Step 2: Form the Routh array for the given characteristic polynomial.
s5 1 2 4
s4 2 4 8
s3 0 0 0
s2
s1
s0
Here, the criterion fails. To remove the above difficulty, the following
method can be used.
226 / 261
Example: 08...
Solution
227 / 261
Example: 08...
Solution
The auxillary equation is
A(s) = 2s4
+ 4s2
+ 8
Differentiate the above auxillary equation,
dA(s)
ds
= 8s3
+ 8s
Now, the array is rewritten as follows.
228 / 261
Example: 08...
Solution
The auxillary equation is
A(s) = 2s4
+ 4s2
+ 8
Differentiate the above auxillary equation,
dA(s)
ds
= 8s3
+ 8s
Now, the array is rewritten as follows.
s5 1 2 4
229 / 261
Example: 08...
Solution
The auxillary equation is
A(s) = 2s4
+ 4s2
+ 8
Differentiate the above auxillary equation,
dA(s)
ds
= 8s3
+ 8s
Now, the array is rewritten as follows.
s5 1 2 4
s4 2 4 8
230 / 261
Example: 08...
Solution
The auxillary equation is
A(s) = 2s4
+ 4s2
+ 8
Differentiate the above auxillary equation,
dA(s)
ds
= 8s3
+ 8s
Now, the array is rewritten as follows.
s5 1 2 4
s4 2 4 8
s3 8 8 0
231 / 261
Example: 08...
Solution
The auxillary equation is
A(s) = 2s4
+ 4s2
+ 8
Differentiate the above auxillary equation,
dA(s)
ds
= 8s3
+ 8s
Now, the array is rewritten as follows.
s5 1 2 4
s4 2 4 8
s3 8 8 0
s2 2 8 0
232 / 261
Example: 08...
Solution
The auxillary equation is
A(s) = 2s4
+ 4s2
+ 8
Differentiate the above auxillary equation,
dA(s)
ds
= 8s3
+ 8s
Now, the array is rewritten as follows.
s5 1 2 4
s4 2 4 8
s3 8 8 0
s2 2 8 0
s1 -24 0
233 / 261
Example: 08...
Solution
The auxillary equation is
A(s) = 2s4
+ 4s2
+ 8
Differentiate the above auxillary equation,
dA(s)
ds
= 8s3
+ 8s
Now, the array is rewritten as follows.
s5 1 2 4
s4 2 4 8
s3 8 8 0
s2 2 8 0
s1 -24 0
s0 8
234 / 261
Example: 08...
Solution
235 / 261
Example: 08...
Solution
Step 3: Verify the sufficient condition for the Routh-Hurwitz stability.
There are two sign changes in first column elements of this
array. Therefore, the system is unstable.
236 / 261
Do it by yourself
237 / 261
Example: 09
Example
238 / 261
Example: 09
Example
Examine stability of the following system given by
s4 + 5s3 + 2s2 + 3s + 2 = 0 using Routh-Hurwitz stability criterion. Find
the number of roots in the right half of the s-plane.
239 / 261
Example: 09
Solution
240 / 261
Example: 09
Solution
Step 1: Verify the necessary condition for the Routh-Hurwitz stability.
All the coefficients of the characteristic polynomial,
B(s) = s4 + 5s3 + 2s2 + 3s + 2 = 0 are positive. So, the control system
satisfies the necessary condition.
241 / 261
Example: 09
Solution
Step 1: Verify the necessary condition for the Routh-Hurwitz stability.
All the coefficients of the characteristic polynomial,
B(s) = s4 + 5s3 + 2s2 + 3s + 2 = 0 are positive. So, the control system
satisfies the necessary condition.
Step 2: Form the Routh array for the given characteristic polynomial.
242 / 261
Example: 09
Solution
Step 1: Verify the necessary condition for the Routh-Hurwitz stability.
All the coefficients of the characteristic polynomial,
B(s) = s4 + 5s3 + 2s2 + 3s + 2 = 0 are positive. So, the control system
satisfies the necessary condition.
Step 2: Form the Routh array for the given characteristic polynomial.
s4 1 2 2
243 / 261
Example: 09
Solution
Step 1: Verify the necessary condition for the Routh-Hurwitz stability.
All the coefficients of the characteristic polynomial,
B(s) = s4 + 5s3 + 2s2 + 3s + 2 = 0 are positive. So, the control system
satisfies the necessary condition.
Step 2: Form the Routh array for the given characteristic polynomial.
s4 1 2 2
s3 5 3 0
244 / 261
Example: 09
Solution
Step 1: Verify the necessary condition for the Routh-Hurwitz stability.
All the coefficients of the characteristic polynomial,
B(s) = s4 + 5s3 + 2s2 + 3s + 2 = 0 are positive. So, the control system
satisfies the necessary condition.
Step 2: Form the Routh array for the given characteristic polynomial.
s4 1 2 2
s3 5 3 0
s2 1.4 2 0
245 / 261
Example: 09
Solution
Step 1: Verify the necessary condition for the Routh-Hurwitz stability.
All the coefficients of the characteristic polynomial,
B(s) = s4 + 5s3 + 2s2 + 3s + 2 = 0 are positive. So, the control system
satisfies the necessary condition.
Step 2: Form the Routh array for the given characteristic polynomial.
s4 1 2 2
s3 5 3 0
s2 1.4 2 0
s1 -4.14 0 0
246 / 261
Example: 09
Solution
Step 1: Verify the necessary condition for the Routh-Hurwitz stability.
All the coefficients of the characteristic polynomial,
B(s) = s4 + 5s3 + 2s2 + 3s + 2 = 0 are positive. So, the control system
satisfies the necessary condition.
Step 2: Form the Routh array for the given characteristic polynomial.
s4 1 2 2
s3 5 3 0
s2 1.4 2 0
s1 -4.14 0 0
s0 0 0 0
247 / 261
Example: 09...
Solution
248 / 261
Example: 09...
Solution
Step 3: Verify the sufficient condition for the Routh-Hurwitz stability.
There are two sign changes in first column elements of this
array. Therefore, the system is unstable. There are two
poles in the right half of the s-plane.
249 / 261
Advantages of Routh-Hurwitz Stability Criterion
1 It offers an easy method of predicting the systems stability without
completely solving the characteristic equation.
250 / 261
Advantages of Routh-Hurwitz Stability Criterion
1 It offers an easy method of predicting the systems stability without
completely solving the characteristic equation.
2 In case, the system is unstable then we can easily get the number of
roots of the characteristic equation that has a positive real part.
251 / 261
Advantages of Routh-Hurwitz Stability Criterion
1 It offers an easy method of predicting the systems stability without
completely solving the characteristic equation.
2 In case, the system is unstable then we can easily get the number of
roots of the characteristic equation that has a positive real part.
3 The time to calculate determinants is saved by the Routh-Hurwitz
criterion.
252 / 261
Advantages of Routh-Hurwitz Stability Criterion
1 It offers an easy method of predicting the systems stability without
completely solving the characteristic equation.
2 In case, the system is unstable then we can easily get the number of
roots of the characteristic equation that has a positive real part.
3 The time to calculate determinants is saved by the Routh-Hurwitz
criterion.
4 By using this we can get the range of values of K.
253 / 261
Advantages of Routh-Hurwitz Stability Criterion
1 It offers an easy method of predicting the systems stability without
completely solving the characteristic equation.
2 In case, the system is unstable then we can easily get the number of
roots of the characteristic equation that has a positive real part.
3 The time to calculate determinants is saved by the Routh-Hurwitz
criterion.
4 By using this we can get the range of values of K.
5 It provides ease of determining the relative stability of the system.
254 / 261
Disadvantages of Routh-Hurwitz Stability Criterion
1 It determines the stability but does not offer the method to stabilize
an unstable system.
255 / 261
Disadvantages of Routh-Hurwitz Stability Criterion
1 It determines the stability but does not offer the method to stabilize
an unstable system.
2 This method suits checking the stability of only linear systems.
256 / 261
Disadvantages of Routh-Hurwitz Stability Criterion
1 It determines the stability but does not offer the method to stabilize
an unstable system.
2 This method suits checking the stability of only linear systems.
3 The accurate position of the closed-loop poles in the s-plane is not
determined.
257 / 261
Disadvantages of Routh-Hurwitz Stability Criterion
1 It determines the stability but does not offer the method to stabilize
an unstable system.
2 This method suits checking the stability of only linear systems.
3 The accurate position of the closed-loop poles in the s-plane is not
determined.
4 It is applicable only when there is a characteristic equation having real
coefficients.
258 / 261
Disadvantages of Routh-Hurwitz Stability Criterion
1 It determines the stability but does not offer the method to stabilize
an unstable system.
2 This method suits checking the stability of only linear systems.
3 The accurate position of the closed-loop poles in the s-plane is not
determined.
4 It is applicable only when there is a characteristic equation having real
coefficients.
5 This is all about checking the stability with the help of the
Routh-Hurwitz stability criterion.
259 / 261
Thank you
Please send your feedback at nbahadure@gmail.com
260 / 261
Thank you
Please send your feedback at nbahadure@gmail.com
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261 / 261

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Control system stability routh hurwitz criterion

  • 1. Control System Stability: Routh Criterion Nilesh Bhaskarrao Bahadure Ph.D, ME, BE nbahadure@gmail.com https://www.sites.google.com/site/nileshbbahadure/home June 29, 2021 1 / 261
  • 2. Overview I 1 Introduction 2 Types of Stable System 3 Routh-Hurwitz Stability Criterion Disadvantages of Hurwitz Criterion Techniques of Routh-Hurwitz criterion 4 Examples 5 Special Cases of Routh Array 6 Advantages and Disadvantages of Routh-Hurwitz Stability Criterion 7 Thank You 2 / 261
  • 3. The Stability of Linear Feedback Systems 3 / 261
  • 4. The Stability of Linear Feedback Systems The issue of ensuring the stability of a closed-loop feedback system is central to control system design. Knowing that an unstable closed-loop system is generally of no practical value, we seek methods to help us analyze and design stable systems. A stable system should exhibit a bounded output if the corresponding input is bounded. 4 / 261
  • 5. The Stability of Linear Feedback Systems... 5 / 261
  • 6. The Stability of Linear Feedback Systems... The stability of a control system is defined as the ability of any system to provide a bounded output when a bounded input is applied to it. More specifically, we can say, that stability allows the system to reach the steady-state and remain in that state for that particular input even after variation in the parameters of the system. 6 / 261
  • 7. The Stability of Linear Feedback Systems... The stability of a control system is defined as the ability of any system to provide a bounded output when a bounded input is applied to it. More specifically, we can say, that stability allows the system to reach the steady-state and remain in that state for that particular input even after variation in the parameters of the system. Stability is considered to be an important property of a control system. It is also referred as the systems ability to reach the steady-state. 7 / 261
  • 8. Stability of Control System 8 / 261
  • 9. Stability of Control System We have already discussed that a stable system generates bounded output for bounded input (BIBO). 9 / 261
  • 10. Stability of Control System We have already discussed that a stable system generates bounded output for bounded input (BIBO). Now the question arises what is bounded signal? Bounded value of a signal represents a finite value. More specifically, we can say, the bounded signal holds a finite value of maxima and minima. Thus, if maxima and minima of any signal are finite then this means all the other values between maxima and minima will also be finite. Suppose we have a signal shown below: Figure : Bounded signal 10 / 261
  • 11. Stability of Control System... 11 / 261
  • 12. Stability of Control System... As we can see that here the maxima and minima of the signal represented above is having finite values. Thus such a signal is said to be bounded and if such an output is provided by a system then it is said to be a stable system. 12 / 261
  • 13. Stability of Control System... As we can see that here the maxima and minima of the signal represented above is having finite values. Thus such a signal is said to be bounded and if such an output is provided by a system then it is said to be a stable system. Therefore, conversely, we can say that an unstable system provides an unbounded output when the applied input is bounded in nature. 13 / 261
  • 14. Stability of Control System... 14 / 261
  • 15. Stability of Control System... Now, what are unbounded signals? 15 / 261
  • 16. Stability of Control System... Now, what are unbounded signals? So, generally, the signals whose graph shows continuous rise thereby showing infinite value such as ramp signal are known as unbounded signals. The figure shown below represents the unbounded signal: Figure : Unbounded signal 16 / 261
  • 17. Stability of Control System... 17 / 261
  • 18. Stability of Control System... Sometimes we come across asymptotically stable systems which are defined as the systems whose output progresses 0, when the input is not present, even when the parameters of the system show variation. 18 / 261
  • 19. Stability of Control System... Sometimes we come across asymptotically stable systems which are defined as the systems whose output progresses 0, when the input is not present, even when the parameters of the system show variation. It is to be noted here that poles of the transfer function, is a factor defining the stability of the control system. 19 / 261
  • 20. How poles can give information regarding the stability of the system? Case I 20 / 261
  • 21. How poles can give information regarding the stability of the system? Case I When the poles of the transfer function of the system are located on the left side of the s-plane then it is said to be a stable system. However, as the poles progress towards 0 or origin, then, in this case, the stability of the system decreases. 21 / 261
  • 22. How poles can give information regarding the stability of the system? Case I When the poles of the transfer function of the system are located on the left side of the s-plane then it is said to be a stable system. However, as the poles progress towards 0 or origin, then, in this case, the stability of the system decreases. Figure : Poles on left side of the s-plane 22 / 261
  • 24. How poles... Case II If for a system, the poles are present in the imaginary axis and are non-repetitive in nature, then it is said to be a marginally stable system. 24 / 261
  • 25. How poles... Case II If for a system, the poles are present in the imaginary axis and are non-repetitive in nature, then it is said to be a marginally stable system. Figure : Poles on imaginary axis s-plane 25 / 261
  • 27. How poles... Case III However, if there exist repetitive poles in the imaginary axis of the s-plane. Then it is called to be an unstable system. 27 / 261
  • 28. How poles... Case III However, if there exist repetitive poles in the imaginary axis of the s-plane. Then it is called to be an unstable system. Figure : Poles on imaginary axis s-plane 28 / 261
  • 30. How poles... Case IV If a system having poles in the right domain of the s-plane, then such a system is called an unstable system. The presence of even a single pole in the right half makes the system unstable. 30 / 261
  • 31. How poles... Case IV If a system having poles in the right domain of the s-plane, then such a system is called an unstable system. The presence of even a single pole in the right half makes the system unstable. Figure : Poles on right hand side of s-plane 31 / 261
  • 32. Absolutely stable system Absolutely stable system 32 / 261
  • 33. Absolutely stable system Absolutely stable system An absolutely stable system is the one that provides bounded output even for the variation in the parameters of the system. This means it is such a system whose output after reaching a steady-state does not show changes irrespective of the disturbances or variation in the system parameter values. 33 / 261
  • 34. Absolutely stable system Absolutely stable system An absolutely stable system is the one that provides bounded output even for the variation in the parameters of the system. This means it is such a system whose output after reaching a steady-state does not show changes irrespective of the disturbances or variation in the system parameter values. The figure shown below represents the step response of an absolutely stable system: 34 / 261
  • 35. Absolutely stable system Absolutely stable system An absolutely stable system is the one that provides bounded output even for the variation in the parameters of the system. This means it is such a system whose output after reaching a steady-state does not show changes irrespective of the disturbances or variation in the system parameter values. The figure shown below represents the step response of an absolutely stable system: 35 / 261
  • 36. Absolutely stable system... Absolutely stable system... 36 / 261
  • 37. Absolutely stable system... Absolutely stable system... The nature of poles for the absolutely stable condition must be real and negative. 37 / 261
  • 38. Absolutely stable system... Absolutely stable system... The nature of poles for the absolutely stable condition must be real and negative. The figure below represents an unstable system: 38 / 261
  • 39. Absolutely stable system... Absolutely stable system... The nature of poles for the absolutely stable condition must be real and negative. The figure below represents an unstable system: Figure : Unstable system 39 / 261
  • 41. Conditionally stable system Conditionally stable system A conditionally stable system gives bounded output for the only specific conditions of the system that is defined by the parameter of the system. 41 / 261
  • 42. Conditionally stable system Conditionally stable system A conditionally stable system gives bounded output for the only specific conditions of the system that is defined by the parameter of the system. Thus we can say here the system exhibits stability only under particular conditions. 42 / 261
  • 43. Conditionally stable system Conditionally stable system A conditionally stable system gives bounded output for the only specific conditions of the system that is defined by the parameter of the system. Thus we can say here the system exhibits stability only under particular conditions. And if that particular condition is violated then the system generates unbounded output. 43 / 261
  • 44. Marginally/ Critically stable system Marginally/ Critically stable system 44 / 261
  • 45. Marginally/ Critically stable system Marginally/ Critically stable system A marginally stable system is the one that generates a signal which is oscillating with constant frequency and amplitude when a bounded input is provided to it. 45 / 261
  • 46. Marginally/ Critically stable system Marginally/ Critically stable system A marginally stable system is the one that generates a signal which is oscillating with constant frequency and amplitude when a bounded input is provided to it. These oscillations are known as sustained oscillations. The figure here represents the step response of a marginally stable system: 46 / 261
  • 47. Marginally/ Critically stable system Marginally/ Critically stable system A marginally stable system is the one that generates a signal which is oscillating with constant frequency and amplitude when a bounded input is provided to it. These oscillations are known as sustained oscillations. The figure here represents the step response of a marginally stable system: Figure : Marginally/ Critically stable system 47 / 261
  • 48. Marginally/ Critically stable system Marginally/ Critically stable system A marginally stable system is the one that generates a signal which is oscillating with constant frequency and amplitude when a bounded input is provided to it. These oscillations are known as sustained oscillations. The figure here represents the step response of a marginally stable system: Figure : Marginally/ Critically stable system 48 / 261
  • 49. Marginally/ Critically stable system Marginally/ Critically stable system A marginally stable system is the one that generates a signal which is oscillating with constant frequency and amplitude when a bounded input is provided to it. These oscillations are known as sustained oscillations. The figure here represents the step response of a marginally stable system: Figure : Marginally/ Critically stable system 49 / 261
  • 50. Marginally/ Critically stable system... 50 / 261
  • 51. Marginally/ Critically stable system... The nature of the closed-loop poles must be non-repetitive and located on the imaginary axis. 51 / 261
  • 52. Marginally/ Critically stable system... The nature of the closed-loop poles must be non-repetitive and located on the imaginary axis. In this way, the stability of the control system is studied. 52 / 261
  • 54. Routh-Hurwitz Stability Criterion Routh-Hurwitz stability criterion is an analytical method used for the determination of stability of a linear time-invariant system. The basis of this criterion revolves around simply determining the location of poles of the characteristic equation in either left half or right half of s-plane despite solving the equation. 54 / 261
  • 55. Routh-Hurwitz Stability Criterion Routh-Hurwitz stability criterion is an analytical method used for the determination of stability of a linear time-invariant system. The basis of this criterion revolves around simply determining the location of poles of the characteristic equation in either left half or right half of s-plane despite solving the equation. The stability of a control system basically defines its ability to reach the steady-state and remain there till the time, specific input is maintained despite the variation in the other factors associated with the system. 55 / 261
  • 56. Routh-Hurwitz Stability Criterion Routh-Hurwitz stability criterion is an analytical method used for the determination of stability of a linear time-invariant system. The basis of this criterion revolves around simply determining the location of poles of the characteristic equation in either left half or right half of s-plane despite solving the equation. The stability of a control system basically defines its ability to reach the steady-state and remain there till the time, specific input is maintained despite the variation in the other factors associated with the system. Thus, to check whether the system is stable or not, the conditions of stability criterion must be satisfied. 56 / 261
  • 58. Routh-Hurwitz Criterion This stability criterion is known to be an algebraic technique that uses the characteristic equation of the transfer function of the closed-loop control system in order to determine its stability. 58 / 261
  • 59. Routh-Hurwitz Criterion This stability criterion is known to be an algebraic technique that uses the characteristic equation of the transfer function of the closed-loop control system in order to determine its stability. According to this criterion, there is a necessary condition and a sufficient condition. 59 / 261
  • 60. Routh-Hurwitz Criterion This stability criterion is known to be an algebraic technique that uses the characteristic equation of the transfer function of the closed-loop control system in order to determine its stability. According to this criterion, there is a necessary condition and a sufficient condition. If the necessary condition is not satisfied by the system, then it is said to be an unstable system. However, even after satisfying the necessary condition, the system may or may not be stable. 60 / 261
  • 61. Routh-Hurwitz Criterion This stability criterion is known to be an algebraic technique that uses the characteristic equation of the transfer function of the closed-loop control system in order to determine its stability. According to this criterion, there is a necessary condition and a sufficient condition. If the necessary condition is not satisfied by the system, then it is said to be an unstable system. However, even after satisfying the necessary condition, the system may or may not be stable. Therefore, we need sufficient condition to determine whether the system is stable or not. 61 / 261
  • 63. Routh-Hurwitz Criterion... Suppose the transfer function of the closed-loop system is given as: C(s) R(s) = b0sm + b1sm−1 + − − − + bm a0sn + a1sn−1 + − − − + an = B(s) F(s) where a and b are the two constants here. 63 / 261
  • 64. Routh-Hurwitz Criterion... Suppose the transfer function of the closed-loop system is given as: C(s) R(s) = b0sm + b1sm−1 + − − − + bm a0sn + a1sn−1 + − − − + an = B(s) F(s) where a and b are the two constants here. On equating F(s) = 0, we will get the closed-loop poles of the system, which is known as the characteristic equation of the system, given as: F(s) = a0sn + a1sn−1 + a2sn−2 + − − − + an = 0 64 / 261
  • 66. Routh-Hurwitz Criterion... Moreover, the roots of this characteristic equation are the poles of the system with the help of which the stability of the system is decided. 66 / 261
  • 67. Routh-Hurwitz Criterion... Moreover, the roots of this characteristic equation are the poles of the system with the help of which the stability of the system is decided. It is to be noted here that before checking the stability of the system using the Routh-Hurwitz criterion, a basic analysis must be done. 67 / 261
  • 68. Routh-Hurwitz Criterion... Moreover, the roots of this characteristic equation are the poles of the system with the help of which the stability of the system is decided. It is to be noted here that before checking the stability of the system using the Routh-Hurwitz criterion, a basic analysis must be done. This general test is simply done by analyzing the characteristic equation, here all the roots of the equation must be present on the left side of the s-plane. 68 / 261
  • 69. Routh-Hurwitz Criterion... The necessary conditions are discussed below: 1 The coefficients of all the polynomials of the equation should be of a similar sign. 69 / 261
  • 70. Routh-Hurwitz Criterion... The necessary conditions are discussed below: 1 The coefficients of all the polynomials of the equation should be of a similar sign. 2 Also, all the coefficients must be present, this means that any of the power of ’s’ from ’n’ to 0 must not be absent. 70 / 261
  • 71. Routh-Hurwitz Criterion... The necessary conditions are discussed below: 1 The coefficients of all the polynomials of the equation should be of a similar sign. 2 Also, all the coefficients must be present, this means that any of the power of ’s’ from ’n’ to 0 must not be absent. 71 / 261
  • 72. Routh-Hurwitz Criterion... The necessary conditions are discussed below: 1 The coefficients of all the polynomials of the equation should be of a similar sign. 2 Also, all the coefficients must be present, this means that any of the power of ’s’ from ’n’ to 0 must not be absent. These two are not sufficient conditions to prove the stability of the system. 72 / 261
  • 73. Routh-Hurwitz Criterion... The necessary conditions are discussed below: 1 The coefficients of all the polynomials of the equation should be of a similar sign. 2 Also, all the coefficients must be present, this means that any of the power of ’s’ from ’n’ to 0 must not be absent. These two are not sufficient conditions to prove the stability of the system. Initially, the sufficient condition to have the poles in the left half of s-plane was proposed by Hurwitz. It was known as Hurwitz criterion and states that all the subdeterminants of the Hurwitz’s determinant must be positive. 73 / 261
  • 74. Disadvantages of Hurwitz Criterion Disadvantages: 1 Solving the determinants of the higher-order system is quite difficult and time-consuming. 74 / 261
  • 75. Disadvantages of Hurwitz Criterion Disadvantages: 1 Solving the determinants of the higher-order system is quite difficult and time-consuming. 2 In the case of an unstable system, the number of roots in the right half of s-plane is non-determinable by this method. 75 / 261
  • 76. Disadvantages of Hurwitz Criterion Disadvantages: 1 Solving the determinants of the higher-order system is quite difficult and time-consuming. 2 In the case of an unstable system, the number of roots in the right half of s-plane is non-determinable by this method. 3 The prediction of marginal stability is not easy. 76 / 261
  • 77. Disadvantages of Hurwitz Criterion Disadvantages: 1 Solving the determinants of the higher-order system is quite difficult and time-consuming. 2 In the case of an unstable system, the number of roots in the right half of s-plane is non-determinable by this method. 3 The prediction of marginal stability is not easy. 77 / 261
  • 78. Disadvantages of Hurwitz Criterion Disadvantages: 1 Solving the determinants of the higher-order system is quite difficult and time-consuming. 2 In the case of an unstable system, the number of roots in the right half of s-plane is non-determinable by this method. 3 The prediction of marginal stability is not easy. So, because of these disadvantages, Routh proposed another technique for determining the stability of the system, this method is generally known as the Routh-Hurwitz criterion or Routh’s criterion. 78 / 261
  • 79. Techniques of Routh-Hurwitz criterion 79 / 261
  • 80. Techniques of Routh-Hurwitz criterion According to Routh, for a stable system the necessary and sufficient condition is that in a routh array, all the terms that are present in the first column must be of the similar sign. This means no change of sign (either from positive to negative or negative to positive) must exist in the first column of the array. 80 / 261
  • 81. Techniques of Routh-Hurwitz criterion According to Routh, for a stable system the necessary and sufficient condition is that in a routh array, all the terms that are present in the first column must be of the similar sign. This means no change of sign (either from positive to negative or negative to positive) must exist in the first column of the array. Therefore, in case if there is any sign change then such a system becomes unstable. 81 / 261
  • 82. Techniques of Routh-Hurwitz criterion According to Routh, for a stable system the necessary and sufficient condition is that in a routh array, all the terms that are present in the first column must be of the similar sign. This means no change of sign (either from positive to negative or negative to positive) must exist in the first column of the array. Therefore, in case if there is any sign change then such a system becomes unstable. This is said on the basis that the overall sign changes in the first column signify the total number of roots lying on the right half of the s-plane, thereby making the system unstable. 82 / 261
  • 83. Techniques of Routh-Hurwitz criterion According to Routh, for a stable system the necessary and sufficient condition is that in a routh array, all the terms that are present in the first column must be of the similar sign. This means no change of sign (either from positive to negative or negative to positive) must exist in the first column of the array. Therefore, in case if there is any sign change then such a system becomes unstable. This is said on the basis that the overall sign changes in the first column signify the total number of roots lying on the right half of the s-plane, thereby making the system unstable. Thus, in simple words, we can say, that for a system to be stable, each coefficient of the first column of the array must have a positive sign. If it is not so, then it is an unstable system. And the number of sign change that makes the system unstable shows the number of poles that are present on the right side of the s-plane. 83 / 261
  • 84. Techniques of Routh-Hurwitz criterion According to Routh, for a stable system the necessary and sufficient condition is that in a routh array, all the terms that are present in the first column must be of the similar sign. This means no change of sign (either from positive to negative or negative to positive) must exist in the first column of the array. Therefore, in case if there is any sign change then such a system becomes unstable. This is said on the basis that the overall sign changes in the first column signify the total number of roots lying on the right half of the s-plane, thereby making the system unstable. Thus, in simple words, we can say, that for a system to be stable, each coefficient of the first column of the array must have a positive sign. If it is not so, then it is an unstable system. And the number of sign change that makes the system unstable shows the number of poles that are present on the right side of the s-plane. This is known as the Routh-Hurwitz Criterion. 84 / 261
  • 85. What is Routh Array? 85 / 261
  • 86. What is Routh Array? Basically, under the Routh-Hurwitz stability criterion, Routh proposed a technique by which the coefficients of the characteristic equation are arranged in a specific manner. This arrangement of the coefficients forms an array which is known as routh array. 86 / 261
  • 87. What is Routh Array? Basically, under the Routh-Hurwitz stability criterion, Routh proposed a technique by which the coefficients of the characteristic equation are arranged in a specific manner. This arrangement of the coefficients forms an array which is known as routh array. Let us now see how a routh array is formed. Consider the general characteristic equation: F(s) = a0sn + a1sn−1 + a2sn−2 + − − − + an = 0 87 / 261
  • 88. What is Routh Array? Basically, under the Routh-Hurwitz stability criterion, Routh proposed a technique by which the coefficients of the characteristic equation are arranged in a specific manner. This arrangement of the coefficients forms an array which is known as routh array. Let us now see how a routh array is formed. Consider the general characteristic equation: F(s) = a0sn + a1sn−1 + a2sn−2 + − − − + an = 0 For the routh array, the first two rows are written from the characteristic equation directly while the rest of the rows are formed with the help of previous rows. 88 / 261
  • 89. What is Routh Array? Basically, under the Routh-Hurwitz stability criterion, Routh proposed a technique by which the coefficients of the characteristic equation are arranged in a specific manner. This arrangement of the coefficients forms an array which is known as routh array. Let us now see how a routh array is formed. Consider the general characteristic equation: F(s) = a0sn + a1sn−1 + a2sn−2 + − − − + an = 0 For the routh array, the first two rows are written from the characteristic equation directly while the rest of the rows are formed with the help of previous rows. It is to be noted here that if in the characteristic equation, n is odd then the first row of the array will hold the odd coefficients. While if n is even then there will be even coefficients present in the first row. 89 / 261
  • 90. What is Routh Array? Basically, under the Routh-Hurwitz stability criterion, Routh proposed a technique by which the coefficients of the characteristic equation are arranged in a specific manner. This arrangement of the coefficients forms an array which is known as routh array. Let us now see how a routh array is formed. Consider the general characteristic equation: F(s) = a0sn + a1sn−1 + a2sn−2 + − − − + an = 0 For the routh array, the first two rows are written from the characteristic equation directly while the rest of the rows are formed with the help of previous rows. It is to be noted here that if in the characteristic equation, n is odd then the first row of the array will hold the odd coefficients. While if n is even then there will be even coefficients present in the first row. In this way, the first and second row of the array will get formed. Let us now see how the rest of the rows will get formed. 90 / 261
  • 91. What is Routh Array?... 91 / 261
  • 92. What is Routh Array?... Figure : Routh Array 92 / 261
  • 93. What is Routh Array?... 93 / 261
  • 94. What is Routh Array?... So, the third row will be formed using the first and second rows. Let us see how 94 / 261
  • 95. What is Routh Array?... So, the third row will be formed using the first and second rows. Let us see how b1 = a1a2 − a0a3 a1 , 95 / 261
  • 96. What is Routh Array?... So, the third row will be formed using the first and second rows. Let us see how b1 = a1a2 − a0a3 a1 , b2 = a1a4 − a0a5 a1 , 96 / 261
  • 97. What is Routh Array?... So, the third row will be formed using the first and second rows. Let us see how b1 = a1a2 − a0a3 a1 , b2 = a1a4 − a0a5 a1 , b3 = a1a6 − a0a7 a1 − −− In a similar way after forming the 3rd row, we can use 2nd and 3rd row to form the 4th row 97 / 261
  • 98. What is Routh Array?... So, the third row will be formed using the first and second rows. Let us see how b1 = a1a2 − a0a3 a1 , b2 = a1a4 − a0a5 a1 , b3 = a1a6 − a0a7 a1 − −− In a similar way after forming the 3rd row, we can use 2nd and 3rd row to form the 4th row c1 = b1a3 − a1b2 b1 , 98 / 261
  • 99. What is Routh Array?... So, the third row will be formed using the first and second rows. Let us see how b1 = a1a2 − a0a3 a1 , b2 = a1a4 − a0a5 a1 , b3 = a1a6 − a0a7 a1 − −− In a similar way after forming the 3rd row, we can use 2nd and 3rd row to form the 4th row c1 = b1a3 − a1b2 b1 , c2 = b1a5 − a1b3 b1 , 99 / 261
  • 100. What is Routh Array?... So, the third row will be formed using the first and second rows. Let us see how b1 = a1a2 − a0a3 a1 , b2 = a1a4 − a0a5 a1 , b3 = a1a6 − a0a7 a1 − −− In a similar way after forming the 3rd row, we can use 2nd and 3rd row to form the 4th row c1 = b1a3 − a1b2 b1 , c2 = b1a5 − a1b3 b1 , c3 = b1a6 − a1b4 b1 − −− and so on. 100 / 261
  • 101. What is Routh Array?... So, the third row will be formed using the first and second rows. Let us see how b1 = a1a2 − a0a3 a1 , b2 = a1a4 − a0a5 a1 , b3 = a1a6 − a0a7 a1 − −− In a similar way after forming the 3rd row, we can use 2nd and 3rd row to form the 4th row c1 = b1a3 − a1b2 b1 , c2 = b1a5 − a1b3 b1 , c3 = b1a6 − a1b4 b1 − −− and so on. Therefore, we have to continue the process until the time we get the coefficients for s0, which is nothing but an. In this way, we get routh array from which the stability of the system is predicted. 101 / 261
  • 102. What is Routh Array?... So, the third row will be formed using the first and second rows. Let us see how b1 = a1a2 − a0a3 a1 , b2 = a1a4 − a0a5 a1 , b3 = a1a6 − a0a7 a1 − −− In a similar way after forming the 3rd row, we can use 2nd and 3rd row to form the 4th row c1 = b1a3 − a1b2 b1 , c2 = b1a5 − a1b3 b1 , c3 = b1a6 − a1b4 b1 − −− and so on. Therefore, we have to continue the process until the time we get the coefficients for s0, which is nothing but an. In this way, we get routh array from which the stability of the system is predicted. Now there are two special cases that cause the failure of the Routh’s test: 102 / 261
  • 103. Two special cases that cause the failure of the Routh’s test Case 1: 103 / 261
  • 104. Two special cases that cause the failure of the Routh’s test Case 1: If in any of the rows the first element is 0 and in the same row even a single non zero element is there then in the next row there will be an infinite term and this will lead to failure of Routh’s test. Case 2: 104 / 261
  • 105. Two special cases that cause the failure of the Routh’s test Case 1: If in any of the rows the first element is 0 and in the same row even a single non zero element is there then in the next row there will be an infinite term and this will lead to failure of Routh’s test. Case 2: If there is such a row in routh array whose all the elements are 0 then it will be impossible to determine the next row and thus the Routh’s test fails in this condition also. This is so because the presence of only 0 in a row shows the absence of coefficients in that particular row. 105 / 261
  • 107. Example: 01 Example find the stability of the control system having characteristic equation, s4 + 3s3 + 3s2 + 2s + 1 = 0 107 / 261
  • 109. Example: 01 Solution Step 1: Verify the necessary condition for the Routh-Hurwitz stability. All the coefficients of the characteristic polynomial, s4 + 3s3 + 3s2 + 2s + 1 are positive. So, the control system satisfies the necessary condition. 109 / 261
  • 110. Example: 01 Solution Step 1: Verify the necessary condition for the Routh-Hurwitz stability. All the coefficients of the characteristic polynomial, s4 + 3s3 + 3s2 + 2s + 1 are positive. So, the control system satisfies the necessary condition. Step 2: Form the Routh array for the given characteristic polynomial. 110 / 261
  • 111. Example: 01 Solution Step 1: Verify the necessary condition for the Routh-Hurwitz stability. All the coefficients of the characteristic polynomial, s4 + 3s3 + 3s2 + 2s + 1 are positive. So, the control system satisfies the necessary condition. Step 2: Form the Routh array for the given characteristic polynomial. s4 1 3 1 111 / 261
  • 112. Example: 01 Solution Step 1: Verify the necessary condition for the Routh-Hurwitz stability. All the coefficients of the characteristic polynomial, s4 + 3s3 + 3s2 + 2s + 1 are positive. So, the control system satisfies the necessary condition. Step 2: Form the Routh array for the given characteristic polynomial. s4 1 3 1 s3 3 2 112 / 261
  • 113. Example: 01 Solution Step 1: Verify the necessary condition for the Routh-Hurwitz stability. All the coefficients of the characteristic polynomial, s4 + 3s3 + 3s2 + 2s + 1 are positive. So, the control system satisfies the necessary condition. Step 2: Form the Routh array for the given characteristic polynomial. s4 1 3 1 s3 3 2 s2 (3∗3)−(2∗1) 3 = 7 3 (3∗1)−(0∗1) 3 = 1 113 / 261
  • 114. Example: 01 Solution Step 1: Verify the necessary condition for the Routh-Hurwitz stability. All the coefficients of the characteristic polynomial, s4 + 3s3 + 3s2 + 2s + 1 are positive. So, the control system satisfies the necessary condition. Step 2: Form the Routh array for the given characteristic polynomial. s4 1 3 1 s3 3 2 s2 (3∗3)−(2∗1) 3 = 7 3 (3∗1)−(0∗1) 3 = 1 s1 ( 7 3 ∗2)−(1∗3) 7 3 = 5 7 114 / 261
  • 115. Example: 01 Solution Step 1: Verify the necessary condition for the Routh-Hurwitz stability. All the coefficients of the characteristic polynomial, s4 + 3s3 + 3s2 + 2s + 1 are positive. So, the control system satisfies the necessary condition. Step 2: Form the Routh array for the given characteristic polynomial. s4 1 3 1 s3 3 2 s2 (3∗3)−(2∗1) 3 = 7 3 (3∗1)−(0∗1) 3 = 1 s1 ( 7 3 ∗2)−(1∗3) 7 3 = 5 7 s0 1 115 / 261
  • 116. Example: 01 Solution Step 1: Verify the necessary condition for the Routh-Hurwitz stability. All the coefficients of the characteristic polynomial, s4 + 3s3 + 3s2 + 2s + 1 are positive. So, the control system satisfies the necessary condition. Step 2: Form the Routh array for the given characteristic polynomial. s4 1 3 1 s3 3 2 s2 (3∗3)−(2∗1) 3 = 7 3 (3∗1)−(0∗1) 3 = 1 s1 ( 7 3 ∗2)−(1∗3) 7 3 = 5 7 s0 1 Step 3: Verify the sufficient condition for the Routh-Hurwitz stability. All the elements of the first column of the Routh array are positive. There is no sign change in the first column of the Routh array. So, the control system is stable. 116 / 261
  • 118. Example: 02 Example Check the stability of the system whose characteristic equation is given by s4 + 2s3 + 6s2 + 4s + 1 = 0 118 / 261
  • 120. Example: 02 Solution Step 1: Verify the necessary condition for the Routh-Hurwitz stability. All the coefficients of the characteristic polynomial, s4 + 2s3 + 6s2 + 4s + 1 = 0 are positive. So, the control system satisfies the necessary condition. 120 / 261
  • 121. Example: 02 Solution Step 1: Verify the necessary condition for the Routh-Hurwitz stability. All the coefficients of the characteristic polynomial, s4 + 2s3 + 6s2 + 4s + 1 = 0 are positive. So, the control system satisfies the necessary condition. Step 2: Form the Routh array for the given characteristic polynomial. 121 / 261
  • 122. Example: 02 Solution Step 1: Verify the necessary condition for the Routh-Hurwitz stability. All the coefficients of the characteristic polynomial, s4 + 2s3 + 6s2 + 4s + 1 = 0 are positive. So, the control system satisfies the necessary condition. Step 2: Form the Routh array for the given characteristic polynomial. s4 1 6 1 122 / 261
  • 123. Example: 02 Solution Step 1: Verify the necessary condition for the Routh-Hurwitz stability. All the coefficients of the characteristic polynomial, s4 + 2s3 + 6s2 + 4s + 1 = 0 are positive. So, the control system satisfies the necessary condition. Step 2: Form the Routh array for the given characteristic polynomial. s4 1 6 1 s3 2 4 123 / 261
  • 124. Example: 02 Solution Step 1: Verify the necessary condition for the Routh-Hurwitz stability. All the coefficients of the characteristic polynomial, s4 + 2s3 + 6s2 + 4s + 1 = 0 are positive. So, the control system satisfies the necessary condition. Step 2: Form the Routh array for the given characteristic polynomial. s4 1 6 1 s3 2 4 s2 (2∗6)−(4∗1) 2 = 4 (2∗1)−(0∗1) 2 = 1 124 / 261
  • 125. Example: 02 Solution Step 1: Verify the necessary condition for the Routh-Hurwitz stability. All the coefficients of the characteristic polynomial, s4 + 2s3 + 6s2 + 4s + 1 = 0 are positive. So, the control system satisfies the necessary condition. Step 2: Form the Routh array for the given characteristic polynomial. s4 1 6 1 s3 2 4 s2 (2∗6)−(4∗1) 2 = 4 (2∗1)−(0∗1) 2 = 1 s1 (4∗4)−(1∗2) 4 = 3.5 125 / 261
  • 126. Example: 02 Solution Step 1: Verify the necessary condition for the Routh-Hurwitz stability. All the coefficients of the characteristic polynomial, s4 + 2s3 + 6s2 + 4s + 1 = 0 are positive. So, the control system satisfies the necessary condition. Step 2: Form the Routh array for the given characteristic polynomial. s4 1 6 1 s3 2 4 s2 (2∗6)−(4∗1) 2 = 4 (2∗1)−(0∗1) 2 = 1 s1 (4∗4)−(1∗2) 4 = 3.5 s0 1 126 / 261
  • 127. Example: 02 Solution Step 1: Verify the necessary condition for the Routh-Hurwitz stability. All the coefficients of the characteristic polynomial, s4 + 2s3 + 6s2 + 4s + 1 = 0 are positive. So, the control system satisfies the necessary condition. Step 2: Form the Routh array for the given characteristic polynomial. s4 1 6 1 s3 2 4 s2 (2∗6)−(4∗1) 2 = 4 (2∗1)−(0∗1) 2 = 1 s1 (4∗4)−(1∗2) 4 = 3.5 s0 1 Step 3: Verify the sufficient condition for the Routh-Hurwitz stability. Since all the coefficients in the first column are of the same sign, i.e., positive, the given equation has no roots with positive real parts; therefore, the system is said to 127 / 261
  • 129. Example: 03 Example Find stability of the following system given by G(s) = K s(s+1) and H(s) = 1 using Routh-Hurwitz stability criterion. 129 / 261
  • 131. Example: 03 Solution In the system T(s) = G(s) 1+G(s)H(s) = K s(s+1) 1+ K s(s+1) Characteristics equation B(s) = s2 + s + K = 0 131 / 261
  • 132. Example: 03 Solution In the system T(s) = G(s) 1+G(s)H(s) = K s(s+1) 1+ K s(s+1) Characteristics equation B(s) = s2 + s + K = 0 Step 1: Verify the necessary condition for the Routh-Hurwitz stability. All the coefficients of the characteristic polynomial, B(s) = s2 + s + K = 0 are positive. So, the control system satisfies the necessary condition (Assuming K > 0). 132 / 261
  • 133. Example: 03 Solution In the system T(s) = G(s) 1+G(s)H(s) = K s(s+1) 1+ K s(s+1) Characteristics equation B(s) = s2 + s + K = 0 Step 1: Verify the necessary condition for the Routh-Hurwitz stability. All the coefficients of the characteristic polynomial, B(s) = s2 + s + K = 0 are positive. So, the control system satisfies the necessary condition (Assuming K > 0). Step 2: Form the Routh array for the given characteristic polynomial. 133 / 261
  • 134. Example: 03 Solution In the system T(s) = G(s) 1+G(s)H(s) = K s(s+1) 1+ K s(s+1) Characteristics equation B(s) = s2 + s + K = 0 Step 1: Verify the necessary condition for the Routh-Hurwitz stability. All the coefficients of the characteristic polynomial, B(s) = s2 + s + K = 0 are positive. So, the control system satisfies the necessary condition (Assuming K > 0). Step 2: Form the Routh array for the given characteristic polynomial. s2 1 K 134 / 261
  • 135. Example: 03 Solution In the system T(s) = G(s) 1+G(s)H(s) = K s(s+1) 1+ K s(s+1) Characteristics equation B(s) = s2 + s + K = 0 Step 1: Verify the necessary condition for the Routh-Hurwitz stability. All the coefficients of the characteristic polynomial, B(s) = s2 + s + K = 0 are positive. So, the control system satisfies the necessary condition (Assuming K > 0). Step 2: Form the Routh array for the given characteristic polynomial. s2 1 K s1 1 0 135 / 261
  • 136. Example: 03 Solution In the system T(s) = G(s) 1+G(s)H(s) = K s(s+1) 1+ K s(s+1) Characteristics equation B(s) = s2 + s + K = 0 Step 1: Verify the necessary condition for the Routh-Hurwitz stability. All the coefficients of the characteristic polynomial, B(s) = s2 + s + K = 0 are positive. So, the control system satisfies the necessary condition (Assuming K > 0). Step 2: Form the Routh array for the given characteristic polynomial. s2 1 K s1 1 0 s0 K 136 / 261
  • 138. Example: 03... Solution Step 3: Verify the sufficient condition for the Routh-Hurwitz stability. There are no sign changes in first column elements of this array.Therefore, the system is always stable for K > 0. 138 / 261
  • 139. Videos on LaTeX, CorelDraw and Many More 139 / 261
  • 141. Example: 04 Example Find stability of the following system given by G(s) = K s(s+2)(s+4) and H(s) = 1 using Routh-Hurwitz stability criterion. 141 / 261
  • 143. Example: 04 Solution In the system T(s) = G(s) 1+G(s)H(s) = K s(s+2)(s+4) 1+ K s(s+2)(s+4) Characteristics equation B(s) = s3 + 6s2 + 8s + K = 0 143 / 261
  • 144. Example: 04 Solution In the system T(s) = G(s) 1+G(s)H(s) = K s(s+2)(s+4) 1+ K s(s+2)(s+4) Characteristics equation B(s) = s3 + 6s2 + 8s + K = 0 Step 1: Verify the necessary condition for the Routh-Hurwitz stability. All the coefficients of the characteristic polynomial, B(s) = s3 + 6s2 + 8s + K = 0 are positive. So, the control system satisfies the necessary condition (Assuming K > 0). 144 / 261
  • 145. Example: 04 Solution In the system T(s) = G(s) 1+G(s)H(s) = K s(s+2)(s+4) 1+ K s(s+2)(s+4) Characteristics equation B(s) = s3 + 6s2 + 8s + K = 0 Step 1: Verify the necessary condition for the Routh-Hurwitz stability. All the coefficients of the characteristic polynomial, B(s) = s3 + 6s2 + 8s + K = 0 are positive. So, the control system satisfies the necessary condition (Assuming K > 0). Step 2: Form the Routh array for the given characteristic polynomial. 145 / 261
  • 146. Example: 04 Solution In the system T(s) = G(s) 1+G(s)H(s) = K s(s+2)(s+4) 1+ K s(s+2)(s+4) Characteristics equation B(s) = s3 + 6s2 + 8s + K = 0 Step 1: Verify the necessary condition for the Routh-Hurwitz stability. All the coefficients of the characteristic polynomial, B(s) = s3 + 6s2 + 8s + K = 0 are positive. So, the control system satisfies the necessary condition (Assuming K > 0). Step 2: Form the Routh array for the given characteristic polynomial. s3 1 8 146 / 261
  • 147. Example: 04 Solution In the system T(s) = G(s) 1+G(s)H(s) = K s(s+2)(s+4) 1+ K s(s+2)(s+4) Characteristics equation B(s) = s3 + 6s2 + 8s + K = 0 Step 1: Verify the necessary condition for the Routh-Hurwitz stability. All the coefficients of the characteristic polynomial, B(s) = s3 + 6s2 + 8s + K = 0 are positive. So, the control system satisfies the necessary condition (Assuming K > 0). Step 2: Form the Routh array for the given characteristic polynomial. s3 1 8 s2 6 K 147 / 261
  • 148. Example: 04 Solution In the system T(s) = G(s) 1+G(s)H(s) = K s(s+2)(s+4) 1+ K s(s+2)(s+4) Characteristics equation B(s) = s3 + 6s2 + 8s + K = 0 Step 1: Verify the necessary condition for the Routh-Hurwitz stability. All the coefficients of the characteristic polynomial, B(s) = s3 + 6s2 + 8s + K = 0 are positive. So, the control system satisfies the necessary condition (Assuming K > 0). Step 2: Form the Routh array for the given characteristic polynomial. s3 1 8 s2 6 K s1 48−K 6 0 148 / 261
  • 149. Example: 04 Solution In the system T(s) = G(s) 1+G(s)H(s) = K s(s+2)(s+4) 1+ K s(s+2)(s+4) Characteristics equation B(s) = s3 + 6s2 + 8s + K = 0 Step 1: Verify the necessary condition for the Routh-Hurwitz stability. All the coefficients of the characteristic polynomial, B(s) = s3 + 6s2 + 8s + K = 0 are positive. So, the control system satisfies the necessary condition (Assuming K > 0). Step 2: Form the Routh array for the given characteristic polynomial. s3 1 8 s2 6 K s1 48−K 6 0 s0 K 149 / 261
  • 151. Example: 04... Solution Step 3: Verify the sufficient condition for the Routh-Hurwitz stability. 151 / 261
  • 152. Example: 04... Solution Step 3: Verify the sufficient condition for the Routh-Hurwitz stability. There are no sign changes in first column elements of this array if K < 48. Therefore, the system is always stable for 0 < K < 48 152 / 261
  • 154. Example: 05 Example Find stability of the following system given by B(s) = s3 + 5s2 + 10s + 3 using Routh-Hurwitz stability criterion. 154 / 261
  • 156. Example: 05 Solution Step 1: Verify the necessary condition for the Routh-Hurwitz stability. All the coefficients of the characteristic polynomial, B(s) = s3 + 5s2 + 10s + 3 = 0 are positive. So, the control system satisfies the necessary condition. 156 / 261
  • 157. Example: 05 Solution Step 1: Verify the necessary condition for the Routh-Hurwitz stability. All the coefficients of the characteristic polynomial, B(s) = s3 + 5s2 + 10s + 3 = 0 are positive. So, the control system satisfies the necessary condition. Step 2: Form the Routh array for the given characteristic polynomial. 157 / 261
  • 158. Example: 05 Solution Step 1: Verify the necessary condition for the Routh-Hurwitz stability. All the coefficients of the characteristic polynomial, B(s) = s3 + 5s2 + 10s + 3 = 0 are positive. So, the control system satisfies the necessary condition. Step 2: Form the Routh array for the given characteristic polynomial. s3 1 10 158 / 261
  • 159. Example: 05 Solution Step 1: Verify the necessary condition for the Routh-Hurwitz stability. All the coefficients of the characteristic polynomial, B(s) = s3 + 5s2 + 10s + 3 = 0 are positive. So, the control system satisfies the necessary condition. Step 2: Form the Routh array for the given characteristic polynomial. s3 1 10 s2 5 3 159 / 261
  • 160. Example: 05 Solution Step 1: Verify the necessary condition for the Routh-Hurwitz stability. All the coefficients of the characteristic polynomial, B(s) = s3 + 5s2 + 10s + 3 = 0 are positive. So, the control system satisfies the necessary condition. Step 2: Form the Routh array for the given characteristic polynomial. s3 1 10 s2 5 3 s1 50−3 5 = 9.4 0 160 / 261
  • 161. Example: 05 Solution Step 1: Verify the necessary condition for the Routh-Hurwitz stability. All the coefficients of the characteristic polynomial, B(s) = s3 + 5s2 + 10s + 3 = 0 are positive. So, the control system satisfies the necessary condition. Step 2: Form the Routh array for the given characteristic polynomial. s3 1 10 s2 5 3 s1 50−3 5 = 9.4 0 s0 3 161 / 261
  • 163. Example: 05... Solution Step 3: Verify the sufficient condition for the Routh-Hurwitz stability. There are no sign changes in first column elements of this array. Therefore, the system is always stable. 163 / 261
  • 164. Do it by yourself 164 / 261
  • 166. Example: 06 Example Find stability of the following system given by B(s) = s3 + 2s2 + 3s + 10 using Routh-Hurwitz stability criterion. 166 / 261
  • 168. Example: 06 Solution Step 1: Verify the necessary condition for the Routh-Hurwitz stability. All the coefficients of the characteristic polynomial, B(s) = s3 + 2s2 + 3s + 10 = 0 are positive. So, the control system satisfies the necessary condition. 168 / 261
  • 169. Example: 06 Solution Step 1: Verify the necessary condition for the Routh-Hurwitz stability. All the coefficients of the characteristic polynomial, B(s) = s3 + 2s2 + 3s + 10 = 0 are positive. So, the control system satisfies the necessary condition. Step 2: Form the Routh array for the given characteristic polynomial. 169 / 261
  • 170. Example: 06 Solution Step 1: Verify the necessary condition for the Routh-Hurwitz stability. All the coefficients of the characteristic polynomial, B(s) = s3 + 2s2 + 3s + 10 = 0 are positive. So, the control system satisfies the necessary condition. Step 2: Form the Routh array for the given characteristic polynomial. s3 1 3 170 / 261
  • 171. Example: 06 Solution Step 1: Verify the necessary condition for the Routh-Hurwitz stability. All the coefficients of the characteristic polynomial, B(s) = s3 + 2s2 + 3s + 10 = 0 are positive. So, the control system satisfies the necessary condition. Step 2: Form the Routh array for the given characteristic polynomial. s3 1 3 s2 2 10 171 / 261
  • 172. Example: 06 Solution Step 1: Verify the necessary condition for the Routh-Hurwitz stability. All the coefficients of the characteristic polynomial, B(s) = s3 + 2s2 + 3s + 10 = 0 are positive. So, the control system satisfies the necessary condition. Step 2: Form the Routh array for the given characteristic polynomial. s3 1 3 s2 2 10 s1 6−10 2 = −2 0 172 / 261
  • 173. Example: 06 Solution Step 1: Verify the necessary condition for the Routh-Hurwitz stability. All the coefficients of the characteristic polynomial, B(s) = s3 + 2s2 + 3s + 10 = 0 are positive. So, the control system satisfies the necessary condition. Step 2: Form the Routh array for the given characteristic polynomial. s3 1 3 s2 2 10 s1 6−10 2 = −2 0 s0 10 173 / 261
  • 175. Example: 06... Solution Step 3: Verify the sufficient condition for the Routh-Hurwitz stability. There are two sign changes in first column elements of this array. Therefore, the system is unstable. 175 / 261
  • 176. Special Cases of Routh Array 176 / 261
  • 177. Special Cases of Routh Array We may come across two types of situations, while forming the Routh table. It is difficult to complete the Routh table from these two situations. 177 / 261
  • 178. Special Cases of Routh Array We may come across two types of situations, while forming the Routh table. It is difficult to complete the Routh table from these two situations. The two special cases are: 1 The first element of any row of the Routh array is zero. 178 / 261
  • 179. Special Cases of Routh Array We may come across two types of situations, while forming the Routh table. It is difficult to complete the Routh table from these two situations. The two special cases are: 1 The first element of any row of the Routh array is zero. 2 All the elements of any row of the Routh array are zero. 179 / 261
  • 180. Case I: First Element of any row of the Routh array is zero 180 / 261
  • 181. Case I: First Element of any row of the Routh array is zero If any row of the Routh array contains only the first element as zero and at least one of the remaining elements have non-zero value, then replace the first element with a small positive integer, . And then continue the process of completing the Routh table. Now, find the number of sign changes in the first column of the Routh table by substituting tends to zero. 181 / 261
  • 183. Example: 07 Example Find stability of the following system given by B(s) = s5 + 2s4 + 4s3 + 8s2 + 3s + 1 using Routh-Hurwitz stability criterion. 183 / 261
  • 185. Example: 07 Solution Step 1: Verify the necessary condition for the Routh-Hurwitz stability. All the coefficients of the characteristic polynomial, B(s) = s5 + 2s4 + 4s3 + 8s2 + 3s + 1 = 0 are positive. So, the control system satisfies the necessary condition. 185 / 261
  • 186. Example: 07 Solution Step 1: Verify the necessary condition for the Routh-Hurwitz stability. All the coefficients of the characteristic polynomial, B(s) = s5 + 2s4 + 4s3 + 8s2 + 3s + 1 = 0 are positive. So, the control system satisfies the necessary condition. Step 2: Form the Routh array for the given characteristic polynomial. 186 / 261
  • 187. Example: 07 Solution Step 1: Verify the necessary condition for the Routh-Hurwitz stability. All the coefficients of the characteristic polynomial, B(s) = s5 + 2s4 + 4s3 + 8s2 + 3s + 1 = 0 are positive. So, the control system satisfies the necessary condition. Step 2: Form the Routh array for the given characteristic polynomial. s5 1 4 3 187 / 261
  • 188. Example: 07 Solution Step 1: Verify the necessary condition for the Routh-Hurwitz stability. All the coefficients of the characteristic polynomial, B(s) = s5 + 2s4 + 4s3 + 8s2 + 3s + 1 = 0 are positive. So, the control system satisfies the necessary condition. Step 2: Form the Routh array for the given characteristic polynomial. s5 1 4 3 s4 2 8 1 188 / 261
  • 189. Example: 07 Solution Step 1: Verify the necessary condition for the Routh-Hurwitz stability. All the coefficients of the characteristic polynomial, B(s) = s5 + 2s4 + 4s3 + 8s2 + 3s + 1 = 0 are positive. So, the control system satisfies the necessary condition. Step 2: Form the Routh array for the given characteristic polynomial. s5 1 4 3 s4 2 8 1 s3 8−8 2 = 0 6−1 2 = 2.5 0 189 / 261
  • 190. Example: 07 Solution Step 1: Verify the necessary condition for the Routh-Hurwitz stability. All the coefficients of the characteristic polynomial, B(s) = s5 + 2s4 + 4s3 + 8s2 + 3s + 1 = 0 are positive. So, the control system satisfies the necessary condition. Step 2: Form the Routh array for the given characteristic polynomial. s5 1 4 3 s4 2 8 1 s3 8−8 2 = 0 6−1 2 = 2.5 0 s2 ∞ 190 / 261
  • 191. Example: 07 Solution Step 1: Verify the necessary condition for the Routh-Hurwitz stability. All the coefficients of the characteristic polynomial, B(s) = s5 + 2s4 + 4s3 + 8s2 + 3s + 1 = 0 are positive. So, the control system satisfies the necessary condition. Step 2: Form the Routh array for the given characteristic polynomial. s5 1 4 3 s4 2 8 1 s3 8−8 2 = 0 6−1 2 = 2.5 0 s2 ∞ s1 191 / 261
  • 192. Example: 07 Solution Step 1: Verify the necessary condition for the Routh-Hurwitz stability. All the coefficients of the characteristic polynomial, B(s) = s5 + 2s4 + 4s3 + 8s2 + 3s + 1 = 0 are positive. So, the control system satisfies the necessary condition. Step 2: Form the Routh array for the given characteristic polynomial. s5 1 4 3 s4 2 8 1 s3 8−8 2 = 0 6−1 2 = 2.5 0 s2 ∞ s1 s0 192 / 261
  • 193. Example: 07 Solution Step 1: Verify the necessary condition for the Routh-Hurwitz stability. All the coefficients of the characteristic polynomial, B(s) = s5 + 2s4 + 4s3 + 8s2 + 3s + 1 = 0 are positive. So, the control system satisfies the necessary condition. Step 2: Form the Routh array for the given characteristic polynomial. s5 1 4 3 s4 2 8 1 s3 8−8 2 = 0 6−1 2 = 2.5 0 s2 ∞ s1 s0 Here, the criterion fails. To remove the above difficulty, the following two methods can be used. 193 / 261
  • 194. Example: 07: Method I Solution 1 Replace 0 by (very small number) and complete the array with . Now, Routh’s array becomes 194 / 261
  • 195. Example: 07: Method I Solution 1 Replace 0 by (very small number) and complete the array with . 2 Examine the sign change by taking → 0 Now, Routh’s array becomes 195 / 261
  • 196. Example: 07: Method I Solution 1 Replace 0 by (very small number) and complete the array with . 2 Examine the sign change by taking → 0 Now, Routh’s array becomes 196 / 261
  • 197. Example: 07: Method I Solution 1 Replace 0 by (very small number) and complete the array with . 2 Examine the sign change by taking → 0 Now, Routh’s array becomes s5 1 4 3 197 / 261
  • 198. Example: 07: Method I Solution 1 Replace 0 by (very small number) and complete the array with . 2 Examine the sign change by taking → 0 Now, Routh’s array becomes s5 1 4 3 s4 2 8 1 198 / 261
  • 199. Example: 07: Method I Solution 1 Replace 0 by (very small number) and complete the array with . 2 Examine the sign change by taking → 0 Now, Routh’s array becomes s5 1 4 3 s4 2 8 1 s3 6−1 2 = 2.5 0 199 / 261
  • 200. Example: 07: Method I Solution 1 Replace 0 by (very small number) and complete the array with . 2 Examine the sign change by taking → 0 Now, Routh’s array becomes s5 1 4 3 s4 2 8 1 s3 6−1 2 = 2.5 0 s2 5−8 1 0 200 / 261
  • 201. Example: 07: Method I Solution 1 Replace 0 by (very small number) and complete the array with . 2 Examine the sign change by taking → 0 Now, Routh’s array becomes s5 1 4 3 s4 2 8 1 s3 6−1 2 = 2.5 0 s2 5−8 1 0 s1 2.5(5−8 )− 5−8 201 / 261
  • 202. Example: 07: Method I Solution 1 Replace 0 by (very small number) and complete the array with . 2 Examine the sign change by taking → 0 Now, Routh’s array becomes s5 1 4 3 s4 2 8 1 s3 6−1 2 = 2.5 0 s2 5−8 1 0 s1 2.5(5−8 )− 5−8 s0 1 202 / 261
  • 204. Example: 07... Solution Step 3: Verify the sufficient condition for the Routh-Hurwitz stability. There are two sign changes in first column elements of this array. Therefore, the system is unstable. 204 / 261
  • 205. Example: 07: Method II Solution 205 / 261
  • 206. Example: 07: Method II Solution Replace s by 1 Z . The system characteristic equation s5 + 2s4 + 4s3 + 8s2 + 3s + 1 = 0 becomes 1 Z5 + 2 Z4 + 4 Z3 + 8 Z2 + 3 Z + 1 = 0 1 + 2Z1 + 4Z2 + 8Z3 + 3Z4 + Z5 Z5 = 0 Z5 + 3Z4 + 8Z3 + 4Z2 + 2Z + 1 = 0 Now, the Routh’s array becomes 206 / 261
  • 207. Example: 07: Method II Solution Replace s by 1 Z . The system characteristic equation s5 + 2s4 + 4s3 + 8s2 + 3s + 1 = 0 becomes 1 Z5 + 2 Z4 + 4 Z3 + 8 Z2 + 3 Z + 1 = 0 1 + 2Z1 + 4Z2 + 8Z3 + 3Z4 + Z5 Z5 = 0 Z5 + 3Z4 + 8Z3 + 4Z2 + 2Z + 1 = 0 Now, the Routh’s array becomes s5 1 8 2 207 / 261
  • 208. Example: 07: Method II Solution Replace s by 1 Z . The system characteristic equation s5 + 2s4 + 4s3 + 8s2 + 3s + 1 = 0 becomes 1 Z5 + 2 Z4 + 4 Z3 + 8 Z2 + 3 Z + 1 = 0 1 + 2Z1 + 4Z2 + 8Z3 + 3Z4 + Z5 Z5 = 0 Z5 + 3Z4 + 8Z3 + 4Z2 + 2Z + 1 = 0 Now, the Routh’s array becomes s5 1 8 2 s4 3 4 1 208 / 261
  • 209. Example: 07: Method II Solution Replace s by 1 Z . The system characteristic equation s5 + 2s4 + 4s3 + 8s2 + 3s + 1 = 0 becomes 1 Z5 + 2 Z4 + 4 Z3 + 8 Z2 + 3 Z + 1 = 0 1 + 2Z1 + 4Z2 + 8Z3 + 3Z4 + Z5 Z5 = 0 Z5 + 3Z4 + 8Z3 + 4Z2 + 2Z + 1 = 0 Now, the Routh’s array becomes s5 1 8 2 s4 3 4 1 s3 6.67 1.67 0 209 / 261
  • 210. Example: 07: Method II Solution Replace s by 1 Z . The system characteristic equation s5 + 2s4 + 4s3 + 8s2 + 3s + 1 = 0 becomes 1 Z5 + 2 Z4 + 4 Z3 + 8 Z2 + 3 Z + 1 = 0 1 + 2Z1 + 4Z2 + 8Z3 + 3Z4 + Z5 Z5 = 0 Z5 + 3Z4 + 8Z3 + 4Z2 + 2Z + 1 = 0 Now, the Routh’s array becomes s5 1 8 2 s4 3 4 1 s3 6.67 1.67 0 s2 3.24 1 0 210 / 261
  • 211. Example: 07: Method II Solution Replace s by 1 Z . The system characteristic equation s5 + 2s4 + 4s3 + 8s2 + 3s + 1 = 0 becomes 1 Z5 + 2 Z4 + 4 Z3 + 8 Z2 + 3 Z + 1 = 0 1 + 2Z1 + 4Z2 + 8Z3 + 3Z4 + Z5 Z5 = 0 Z5 + 3Z4 + 8Z3 + 4Z2 + 2Z + 1 = 0 Now, the Routh’s array becomes s5 1 8 2 s4 3 4 1 s3 6.67 1.67 0 s2 3.24 1 0 s1 -0.388 0 0 211 / 261
  • 212. Example: 07: Method II Solution Replace s by 1 Z . The system characteristic equation s5 + 2s4 + 4s3 + 8s2 + 3s + 1 = 0 becomes 1 Z5 + 2 Z4 + 4 Z3 + 8 Z2 + 3 Z + 1 = 0 1 + 2Z1 + 4Z2 + 8Z3 + 3Z4 + Z5 Z5 = 0 Z5 + 3Z4 + 8Z3 + 4Z2 + 2Z + 1 = 0 Now, the Routh’s array becomes s5 1 8 2 s4 3 4 1 s3 6.67 1.67 0 s2 3.24 1 0 s1 -0.388 0 0 s0 1 0 0 There are two sign changes in first column elements of this array. Therefore, the system is unstable. 212 / 261
  • 213. Case II: All Elements of any row of the Routh array is zero 213 / 261
  • 214. Case II: All Elements of any row of the Routh array is zero If there is such a row in Routh array whose all the elements are 0 then it will be impossible to determine the next row and thus the Rouths test fails in this condition also. This is so because the presence of only 0 in a row shows the absence of coefficients in that particular row. 214 / 261
  • 216. Example: 08 Example Find stability of the following system given by B(s) = s5 + 2s4 + 2s3 + 4s2 + 4s + 8 using Routh-Hurwitz stability criterion. 216 / 261
  • 218. Example: 08 Solution Step 1: Verify the necessary condition for the Routh-Hurwitz stability. All the coefficients of the characteristic polynomial, B(s) = s5 + 2s4 + 2s3 + 4s2 + 4s + 8 = 0 are positive. So, the control system satisfies the necessary condition. 218 / 261
  • 219. Example: 08 Solution Step 1: Verify the necessary condition for the Routh-Hurwitz stability. All the coefficients of the characteristic polynomial, B(s) = s5 + 2s4 + 2s3 + 4s2 + 4s + 8 = 0 are positive. So, the control system satisfies the necessary condition. Step 2: Form the Routh array for the given characteristic polynomial. 219 / 261
  • 220. Example: 08 Solution Step 1: Verify the necessary condition for the Routh-Hurwitz stability. All the coefficients of the characteristic polynomial, B(s) = s5 + 2s4 + 2s3 + 4s2 + 4s + 8 = 0 are positive. So, the control system satisfies the necessary condition. Step 2: Form the Routh array for the given characteristic polynomial. s5 1 2 4 220 / 261
  • 221. Example: 08 Solution Step 1: Verify the necessary condition for the Routh-Hurwitz stability. All the coefficients of the characteristic polynomial, B(s) = s5 + 2s4 + 2s3 + 4s2 + 4s + 8 = 0 are positive. So, the control system satisfies the necessary condition. Step 2: Form the Routh array for the given characteristic polynomial. s5 1 2 4 s4 2 4 8 221 / 261
  • 222. Example: 08 Solution Step 1: Verify the necessary condition for the Routh-Hurwitz stability. All the coefficients of the characteristic polynomial, B(s) = s5 + 2s4 + 2s3 + 4s2 + 4s + 8 = 0 are positive. So, the control system satisfies the necessary condition. Step 2: Form the Routh array for the given characteristic polynomial. s5 1 2 4 s4 2 4 8 s3 0 0 0 222 / 261
  • 223. Example: 08 Solution Step 1: Verify the necessary condition for the Routh-Hurwitz stability. All the coefficients of the characteristic polynomial, B(s) = s5 + 2s4 + 2s3 + 4s2 + 4s + 8 = 0 are positive. So, the control system satisfies the necessary condition. Step 2: Form the Routh array for the given characteristic polynomial. s5 1 2 4 s4 2 4 8 s3 0 0 0 s2 223 / 261
  • 224. Example: 08 Solution Step 1: Verify the necessary condition for the Routh-Hurwitz stability. All the coefficients of the characteristic polynomial, B(s) = s5 + 2s4 + 2s3 + 4s2 + 4s + 8 = 0 are positive. So, the control system satisfies the necessary condition. Step 2: Form the Routh array for the given characteristic polynomial. s5 1 2 4 s4 2 4 8 s3 0 0 0 s2 s1 224 / 261
  • 225. Example: 08 Solution Step 1: Verify the necessary condition for the Routh-Hurwitz stability. All the coefficients of the characteristic polynomial, B(s) = s5 + 2s4 + 2s3 + 4s2 + 4s + 8 = 0 are positive. So, the control system satisfies the necessary condition. Step 2: Form the Routh array for the given characteristic polynomial. s5 1 2 4 s4 2 4 8 s3 0 0 0 s2 s1 s0 225 / 261
  • 226. Example: 08 Solution Step 1: Verify the necessary condition for the Routh-Hurwitz stability. All the coefficients of the characteristic polynomial, B(s) = s5 + 2s4 + 2s3 + 4s2 + 4s + 8 = 0 are positive. So, the control system satisfies the necessary condition. Step 2: Form the Routh array for the given characteristic polynomial. s5 1 2 4 s4 2 4 8 s3 0 0 0 s2 s1 s0 Here, the criterion fails. To remove the above difficulty, the following method can be used. 226 / 261
  • 228. Example: 08... Solution The auxillary equation is A(s) = 2s4 + 4s2 + 8 Differentiate the above auxillary equation, dA(s) ds = 8s3 + 8s Now, the array is rewritten as follows. 228 / 261
  • 229. Example: 08... Solution The auxillary equation is A(s) = 2s4 + 4s2 + 8 Differentiate the above auxillary equation, dA(s) ds = 8s3 + 8s Now, the array is rewritten as follows. s5 1 2 4 229 / 261
  • 230. Example: 08... Solution The auxillary equation is A(s) = 2s4 + 4s2 + 8 Differentiate the above auxillary equation, dA(s) ds = 8s3 + 8s Now, the array is rewritten as follows. s5 1 2 4 s4 2 4 8 230 / 261
  • 231. Example: 08... Solution The auxillary equation is A(s) = 2s4 + 4s2 + 8 Differentiate the above auxillary equation, dA(s) ds = 8s3 + 8s Now, the array is rewritten as follows. s5 1 2 4 s4 2 4 8 s3 8 8 0 231 / 261
  • 232. Example: 08... Solution The auxillary equation is A(s) = 2s4 + 4s2 + 8 Differentiate the above auxillary equation, dA(s) ds = 8s3 + 8s Now, the array is rewritten as follows. s5 1 2 4 s4 2 4 8 s3 8 8 0 s2 2 8 0 232 / 261
  • 233. Example: 08... Solution The auxillary equation is A(s) = 2s4 + 4s2 + 8 Differentiate the above auxillary equation, dA(s) ds = 8s3 + 8s Now, the array is rewritten as follows. s5 1 2 4 s4 2 4 8 s3 8 8 0 s2 2 8 0 s1 -24 0 233 / 261
  • 234. Example: 08... Solution The auxillary equation is A(s) = 2s4 + 4s2 + 8 Differentiate the above auxillary equation, dA(s) ds = 8s3 + 8s Now, the array is rewritten as follows. s5 1 2 4 s4 2 4 8 s3 8 8 0 s2 2 8 0 s1 -24 0 s0 8 234 / 261
  • 236. Example: 08... Solution Step 3: Verify the sufficient condition for the Routh-Hurwitz stability. There are two sign changes in first column elements of this array. Therefore, the system is unstable. 236 / 261
  • 237. Do it by yourself 237 / 261
  • 239. Example: 09 Example Examine stability of the following system given by s4 + 5s3 + 2s2 + 3s + 2 = 0 using Routh-Hurwitz stability criterion. Find the number of roots in the right half of the s-plane. 239 / 261
  • 241. Example: 09 Solution Step 1: Verify the necessary condition for the Routh-Hurwitz stability. All the coefficients of the characteristic polynomial, B(s) = s4 + 5s3 + 2s2 + 3s + 2 = 0 are positive. So, the control system satisfies the necessary condition. 241 / 261
  • 242. Example: 09 Solution Step 1: Verify the necessary condition for the Routh-Hurwitz stability. All the coefficients of the characteristic polynomial, B(s) = s4 + 5s3 + 2s2 + 3s + 2 = 0 are positive. So, the control system satisfies the necessary condition. Step 2: Form the Routh array for the given characteristic polynomial. 242 / 261
  • 243. Example: 09 Solution Step 1: Verify the necessary condition for the Routh-Hurwitz stability. All the coefficients of the characteristic polynomial, B(s) = s4 + 5s3 + 2s2 + 3s + 2 = 0 are positive. So, the control system satisfies the necessary condition. Step 2: Form the Routh array for the given characteristic polynomial. s4 1 2 2 243 / 261
  • 244. Example: 09 Solution Step 1: Verify the necessary condition for the Routh-Hurwitz stability. All the coefficients of the characteristic polynomial, B(s) = s4 + 5s3 + 2s2 + 3s + 2 = 0 are positive. So, the control system satisfies the necessary condition. Step 2: Form the Routh array for the given characteristic polynomial. s4 1 2 2 s3 5 3 0 244 / 261
  • 245. Example: 09 Solution Step 1: Verify the necessary condition for the Routh-Hurwitz stability. All the coefficients of the characteristic polynomial, B(s) = s4 + 5s3 + 2s2 + 3s + 2 = 0 are positive. So, the control system satisfies the necessary condition. Step 2: Form the Routh array for the given characteristic polynomial. s4 1 2 2 s3 5 3 0 s2 1.4 2 0 245 / 261
  • 246. Example: 09 Solution Step 1: Verify the necessary condition for the Routh-Hurwitz stability. All the coefficients of the characteristic polynomial, B(s) = s4 + 5s3 + 2s2 + 3s + 2 = 0 are positive. So, the control system satisfies the necessary condition. Step 2: Form the Routh array for the given characteristic polynomial. s4 1 2 2 s3 5 3 0 s2 1.4 2 0 s1 -4.14 0 0 246 / 261
  • 247. Example: 09 Solution Step 1: Verify the necessary condition for the Routh-Hurwitz stability. All the coefficients of the characteristic polynomial, B(s) = s4 + 5s3 + 2s2 + 3s + 2 = 0 are positive. So, the control system satisfies the necessary condition. Step 2: Form the Routh array for the given characteristic polynomial. s4 1 2 2 s3 5 3 0 s2 1.4 2 0 s1 -4.14 0 0 s0 0 0 0 247 / 261
  • 249. Example: 09... Solution Step 3: Verify the sufficient condition for the Routh-Hurwitz stability. There are two sign changes in first column elements of this array. Therefore, the system is unstable. There are two poles in the right half of the s-plane. 249 / 261
  • 250. Advantages of Routh-Hurwitz Stability Criterion 1 It offers an easy method of predicting the systems stability without completely solving the characteristic equation. 250 / 261
  • 251. Advantages of Routh-Hurwitz Stability Criterion 1 It offers an easy method of predicting the systems stability without completely solving the characteristic equation. 2 In case, the system is unstable then we can easily get the number of roots of the characteristic equation that has a positive real part. 251 / 261
  • 252. Advantages of Routh-Hurwitz Stability Criterion 1 It offers an easy method of predicting the systems stability without completely solving the characteristic equation. 2 In case, the system is unstable then we can easily get the number of roots of the characteristic equation that has a positive real part. 3 The time to calculate determinants is saved by the Routh-Hurwitz criterion. 252 / 261
  • 253. Advantages of Routh-Hurwitz Stability Criterion 1 It offers an easy method of predicting the systems stability without completely solving the characteristic equation. 2 In case, the system is unstable then we can easily get the number of roots of the characteristic equation that has a positive real part. 3 The time to calculate determinants is saved by the Routh-Hurwitz criterion. 4 By using this we can get the range of values of K. 253 / 261
  • 254. Advantages of Routh-Hurwitz Stability Criterion 1 It offers an easy method of predicting the systems stability without completely solving the characteristic equation. 2 In case, the system is unstable then we can easily get the number of roots of the characteristic equation that has a positive real part. 3 The time to calculate determinants is saved by the Routh-Hurwitz criterion. 4 By using this we can get the range of values of K. 5 It provides ease of determining the relative stability of the system. 254 / 261
  • 255. Disadvantages of Routh-Hurwitz Stability Criterion 1 It determines the stability but does not offer the method to stabilize an unstable system. 255 / 261
  • 256. Disadvantages of Routh-Hurwitz Stability Criterion 1 It determines the stability but does not offer the method to stabilize an unstable system. 2 This method suits checking the stability of only linear systems. 256 / 261
  • 257. Disadvantages of Routh-Hurwitz Stability Criterion 1 It determines the stability but does not offer the method to stabilize an unstable system. 2 This method suits checking the stability of only linear systems. 3 The accurate position of the closed-loop poles in the s-plane is not determined. 257 / 261
  • 258. Disadvantages of Routh-Hurwitz Stability Criterion 1 It determines the stability but does not offer the method to stabilize an unstable system. 2 This method suits checking the stability of only linear systems. 3 The accurate position of the closed-loop poles in the s-plane is not determined. 4 It is applicable only when there is a characteristic equation having real coefficients. 258 / 261
  • 259. Disadvantages of Routh-Hurwitz Stability Criterion 1 It determines the stability but does not offer the method to stabilize an unstable system. 2 This method suits checking the stability of only linear systems. 3 The accurate position of the closed-loop poles in the s-plane is not determined. 4 It is applicable only when there is a characteristic equation having real coefficients. 5 This is all about checking the stability with the help of the Routh-Hurwitz stability criterion. 259 / 261
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