Introduction, Types of Stable System, Routh-Hurwitz Stability Criterion, Disadvantages of Hurwitz Criterion, Techniques of Routh-Hurwitz criterion, Examples, Special Cases of Routh Array, Advantages and Disadvantages of Routh-Hurwitz Stability Criterion, and examples.
It gives how states are representing in various canonical forms and how it it is different from transfer function approach. and finally test the system controllability and observability by kalman's test
Process load,process lag,self regulation,error,control lag,dead time,cycling,discontinious control modes,two position control modes,flaoting control modes,propotional band,offset,propotional control, integral control,derivative control,pid control,pi control,pd control,tuning of pid control
Ch5 transient and steady state response analyses(control)Elaf A.Saeed
Chapter 5 Transient and steady-state response analyses. From the book (Ogata Modern Control Engineering 5th).
5-1 introduction.
5-2 First-Order System.
5-3 second-order system.
5-6 Routh’s stability criterion.
5-8 Steady-state errors in unity-feedback control systems.
It gives how states are representing in various canonical forms and how it it is different from transfer function approach. and finally test the system controllability and observability by kalman's test
Process load,process lag,self regulation,error,control lag,dead time,cycling,discontinious control modes,two position control modes,flaoting control modes,propotional band,offset,propotional control, integral control,derivative control,pid control,pi control,pd control,tuning of pid control
Ch5 transient and steady state response analyses(control)Elaf A.Saeed
Chapter 5 Transient and steady-state response analyses. From the book (Ogata Modern Control Engineering 5th).
5-1 introduction.
5-2 First-Order System.
5-3 second-order system.
5-6 Routh’s stability criterion.
5-8 Steady-state errors in unity-feedback control systems.
Root locus is a graphical representation of the closed-loop poles as a system parameter is varied.
It can be used to describe qualitatively the performance of a system as various parameters are changed.
It gives graphic representation of a system’s transient response and also stability.
We can see the range of stability, instability, and the conditions that cause a system to break into oscillation.
This Presentation explains about the introduction of Frequency Response Analysis. This video clearly shows advantages and disadvantages of Frequency Response Analysis and also explains frequency domain specifications and derivations of Resonant Peak, Resonant Frequency and Bandwidth.
Ch2 mathematical modeling of control system Elaf A.Saeed
Chapter 2 Mathematical modeling of control system From the book (Ogata Modern Control Engineering 5th).
2-1 introduction.
2-2 transfer function and impulse response function.
2-3 automatic control systems.
This presentation explains about the introduction of Bode Plot, advantages of bode plot and also steps to draw Bode plot (Magnitude plot and phase plot). It explains basic or key factors used for drawing Bode plot. It also explains how to determine Magnitude, phase and slope for basic factors. It also explains how to determine stability by using Bode Plot and also how to determine Gain Crossover Frequency and Phase Crossover Frequency, Gain Margin and Phase Margin. It also explains drawing Bode plot with an example and also determines stability by using Bode Plot and also determines Gain Crossover Frequency and Phase Crossover Frequency, Gain Margin and Phase Margin.
Part of Lecture Series on Automatic Control Systems delivered by me to Final year Diploma in Engg. Students. Equally useful for higher level. Easy language and step by step procedure for drawing Bode Plots. Three illustrative examples are included.
Transfer Function, Concepts of stability(critical, Absolute & Relative) Poles...Waqas Afzal
Transfer Function
The Order of Control Systems
Concepts of stability(critical, Absolute & Relative)
Poles, Zeros
Stability calculation
BIBO stability
Transient Response Characteristics
Biomedical Control Systems - THE CONCEPT OF STABILITY & ROOT LOCUS TECHNIQUE ...Mathankumar S
Biomedical control systems - THE CONCEPT OF STABILITY & ROOT LOCUS TECHNIQUE (short Questions & Answers) - ITS DEALS WITH STABILITY OF THE SYSTEM (ROUTH HURWITZ CRITERION, ROUTH ARRAY), ROOT LOCUS TECHNIQUE, ZEROS & POLES,
Root locus is a graphical representation of the closed-loop poles as a system parameter is varied.
It can be used to describe qualitatively the performance of a system as various parameters are changed.
It gives graphic representation of a system’s transient response and also stability.
We can see the range of stability, instability, and the conditions that cause a system to break into oscillation.
This Presentation explains about the introduction of Frequency Response Analysis. This video clearly shows advantages and disadvantages of Frequency Response Analysis and also explains frequency domain specifications and derivations of Resonant Peak, Resonant Frequency and Bandwidth.
Ch2 mathematical modeling of control system Elaf A.Saeed
Chapter 2 Mathematical modeling of control system From the book (Ogata Modern Control Engineering 5th).
2-1 introduction.
2-2 transfer function and impulse response function.
2-3 automatic control systems.
This presentation explains about the introduction of Bode Plot, advantages of bode plot and also steps to draw Bode plot (Magnitude plot and phase plot). It explains basic or key factors used for drawing Bode plot. It also explains how to determine Magnitude, phase and slope for basic factors. It also explains how to determine stability by using Bode Plot and also how to determine Gain Crossover Frequency and Phase Crossover Frequency, Gain Margin and Phase Margin. It also explains drawing Bode plot with an example and also determines stability by using Bode Plot and also determines Gain Crossover Frequency and Phase Crossover Frequency, Gain Margin and Phase Margin.
Part of Lecture Series on Automatic Control Systems delivered by me to Final year Diploma in Engg. Students. Equally useful for higher level. Easy language and step by step procedure for drawing Bode Plots. Three illustrative examples are included.
Transfer Function, Concepts of stability(critical, Absolute & Relative) Poles...Waqas Afzal
Transfer Function
The Order of Control Systems
Concepts of stability(critical, Absolute & Relative)
Poles, Zeros
Stability calculation
BIBO stability
Transient Response Characteristics
Biomedical Control Systems - THE CONCEPT OF STABILITY & ROOT LOCUS TECHNIQUE ...Mathankumar S
Biomedical control systems - THE CONCEPT OF STABILITY & ROOT LOCUS TECHNIQUE (short Questions & Answers) - ITS DEALS WITH STABILITY OF THE SYSTEM (ROUTH HURWITZ CRITERION, ROUTH ARRAY), ROOT LOCUS TECHNIQUE, ZEROS & POLES,
Here is a quick review of the topic- Stability in Control System that might help you.
**A system is said to be stable, if its output is under control. Otherwise, it is said to be unstable**
In this presentation we have,
- Intro of Stability
-Types of System
- Concept of Stability
- Routh Hurwitz Criteria
- Limitations of Hurwitz Criterion
- Concluded
Hope this will be beneficial.
Thanking in anticipation.
Robust Fuzzy Output Feedback Controller for Affine Nonlinear Systems via T–S ...Mostafa Shokrian Zeini
This presentation concerns the design of a robust H_∞ fuzzy output feedback controller for a class of affine nonlinear systems with disturbance via Takagi-Sugeno (T–S) fuzzy bilinear model. The parallel distributed compensation (PDC) technique is utilized to design a fuzzy controller. The stability conditions of the overall closed loop T-S fuzzy bilinear model are formulated in terms of Lyapunov function via linear matrix inequality (LMI). The control law is robustified by H_∞ sense to attenuate external disturbance. Moreover, the desired controller gains can be obtained by solving a set of LMI.
This formula book gives simple and useful formulas related to control system. It helps students in solving numerical problems, in their competitive examinations
Basic Elements of Control System, Open loop and Closed loop systems, Differential
equations and Transfer function, Modeling of Electric systems, Translational and rotational
mechanical systems, Block diagram reduction Techniques, Signal flow graph
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• Compatible with Backplane mount serial communication.
• Compatible with commercial and Defence aviation CCR system.
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• Indigenized local Support/presence in India.
• Easy in configuration using DIP switches.
Technical Specifications
Indigenized remote control interface card suitable for MAFI system CCR equipment. Compatible for IDM8000 CCR. Backplane mounted serial and TCP/Ethernet communication module for CCR remote access. IDM 8000 CCR remote control on serial and TCP protocol.
Key Features
Indigenized remote control interface card suitable for MAFI system CCR equipment. Compatible for IDM8000 CCR. Backplane mounted serial and TCP/Ethernet communication module for CCR remote access. IDM 8000 CCR remote control on serial and TCP protocol.
• Remote control: Parallel or serial interface
• Compatible with MAFI CCR system
• Copatiable with IDM8000 CCR
• Compatible with Backplane mount serial communication.
• Compatible with commercial and Defence aviation CCR system.
• Remote control system for accessing CCR and allied system over serial or TCP.
• Indigenized local Support/presence in India.
Application
• Remote control: Parallel or serial interface.
• Compatible with MAFI CCR system.
• Compatible with IDM8000 CCR.
• Compatible with Backplane mount serial communication.
• Compatible with commercial and Defence aviation CCR system.
• Remote control system for accessing CCR and allied system over serial or TCP.
• Indigenized local Support/presence in India.
• Easy in configuration using DIP switches.
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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
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
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
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
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
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
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
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
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
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
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.
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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.
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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
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
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
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
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
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
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
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
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
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
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
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
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
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.
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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.
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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.
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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.
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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