This document provides an overview of stability analysis in the frequency domain, including absolute stability, relative stability, Routh's stability criterion, and the root locus method. It defines absolute and relative stability and describes how Routh's stability criterion can be used to determine absolute stability by analyzing the signs of coefficients in a characteristic equation. The document also introduces the root locus method for analyzing how closed-loop poles move in the s-plane as the loop gain is varied.
This document discusses stability analysis in the frequency domain using Routh's stability criterion. It defines absolute and relative stability and explains that Routh's criterion determines stability by analyzing the signs of coefficients in the characteristic equation's Routh array. The document provides examples of applying Routh's criterion to determine stability and calculating the range of a parameter value for stability. It also covers special cases and using the criterion to analyze relative stability by shifting the s-plane.
ME-314 Introduction to Control Engineering is a course taught to Mechanical Engineering senior undergrads. The course is taught by Dr. Bilal Siddiqui at DHA Suffa University. This lecture is about basic rules of sketching root locus.
NONLINEAR CONTROL SYSTEM(Phase plane & Phase Trajectory Method)Niraj Solanki
This document discusses nonlinear control systems using phase plane and phase trajectory methods. It defines nonlinear systems and common physical nonlinearities like saturation, dead zone, relay, and backlash. Phase plane analysis is introduced as a graphical method to study nonlinear systems using a plane with state variables x and dx/dt. Key concepts are defined like phase plane, phase trajectory, and phase portrait. Methods for sketching phase trajectories include analytical solutions and graphical methods using isoclines. Examples are given to illustrate phase portraits for different linear systems.
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.
The document discusses several properties and analysis/control techniques for non-linear systems. Some key points:
- Non-linear systems do not follow superposition and may have multiple equilibria, unlike linear systems which have a single equilibrium. They can also exhibit phenomena like limit cycles, bifurcations, and chaos.
- Techniques for analyzing non-linear systems include describing function methods, phase plane analysis, Lyapunov stability analysis, and singular perturbation methods.
- Control design techniques for non-linear systems include gain scheduling, adaptive control, feedback linearization, and sliding mode control. These aim to treat the system as linear over limited operating ranges or introduce auxiliary feedback to achieve linearization.
Chapter 7 Controls Systems Analysis and Design by the frequency response analysis . From the book (Ogata Modern Control Engineering 5th).
7-1 introduction.
7-2 Bode diagrams.
The document discusses different types of singular points in control systems:
1. A nodal point occurs when both eigenvalues are real and negative, causing all trajectories to converge to the origin in a stable manner.
2. A saddle point occurs when the eigenvalues are real and equal but opposite in sign, making the origin unstable with some trajectories converging and others diverging.
3. A focus point occurs when the eigenvalues are complex conjugates with negative real parts, causing the trajectories to spiral inward in a stable manner towards the origin.
4. A center or vortex point occurs when the eigenvalues are purely imaginary, causing the trajectories to travel in closed paths around the origin in a limitedly stable manner.
ME-314 Introduction to Control Engineering is a course taught to Mechanical Engineering senior undergrads. The course is taught by Dr. Bilal Siddiqui at DHA Suffa University. This lecture is about time response of systems derived by inspection of poles and zeros. First and second order systems are considered, along with higher order and nonminimum phase systems
This document discusses stability analysis in the frequency domain using Routh's stability criterion. It defines absolute and relative stability and explains that Routh's criterion determines stability by analyzing the signs of coefficients in the characteristic equation's Routh array. The document provides examples of applying Routh's criterion to determine stability and calculating the range of a parameter value for stability. It also covers special cases and using the criterion to analyze relative stability by shifting the s-plane.
ME-314 Introduction to Control Engineering is a course taught to Mechanical Engineering senior undergrads. The course is taught by Dr. Bilal Siddiqui at DHA Suffa University. This lecture is about basic rules of sketching root locus.
NONLINEAR CONTROL SYSTEM(Phase plane & Phase Trajectory Method)Niraj Solanki
This document discusses nonlinear control systems using phase plane and phase trajectory methods. It defines nonlinear systems and common physical nonlinearities like saturation, dead zone, relay, and backlash. Phase plane analysis is introduced as a graphical method to study nonlinear systems using a plane with state variables x and dx/dt. Key concepts are defined like phase plane, phase trajectory, and phase portrait. Methods for sketching phase trajectories include analytical solutions and graphical methods using isoclines. Examples are given to illustrate phase portraits for different linear systems.
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.
The document discusses several properties and analysis/control techniques for non-linear systems. Some key points:
- Non-linear systems do not follow superposition and may have multiple equilibria, unlike linear systems which have a single equilibrium. They can also exhibit phenomena like limit cycles, bifurcations, and chaos.
- Techniques for analyzing non-linear systems include describing function methods, phase plane analysis, Lyapunov stability analysis, and singular perturbation methods.
- Control design techniques for non-linear systems include gain scheduling, adaptive control, feedback linearization, and sliding mode control. These aim to treat the system as linear over limited operating ranges or introduce auxiliary feedback to achieve linearization.
Chapter 7 Controls Systems Analysis and Design by the frequency response analysis . From the book (Ogata Modern Control Engineering 5th).
7-1 introduction.
7-2 Bode diagrams.
The document discusses different types of singular points in control systems:
1. A nodal point occurs when both eigenvalues are real and negative, causing all trajectories to converge to the origin in a stable manner.
2. A saddle point occurs when the eigenvalues are real and equal but opposite in sign, making the origin unstable with some trajectories converging and others diverging.
3. A focus point occurs when the eigenvalues are complex conjugates with negative real parts, causing the trajectories to spiral inward in a stable manner towards the origin.
4. A center or vortex point occurs when the eigenvalues are purely imaginary, causing the trajectories to travel in closed paths around the origin in a limitedly stable manner.
ME-314 Introduction to Control Engineering is a course taught to Mechanical Engineering senior undergrads. The course is taught by Dr. Bilal Siddiqui at DHA Suffa University. This lecture is about time response of systems derived by inspection of poles and zeros. First and second order systems are considered, along with higher order and nonminimum phase systems
This document provides an overview of transfer functions and stability analysis of linear time-invariant (LTI) systems. It discusses how the Laplace transform can be used to represent signals as algebraic functions and calculate transfer functions as the ratio of the Laplace transforms of the output and input. Poles and zeros are introduced as important factors for stability. A system is stable if all its poles reside in the left half of the s-plane and unstable if any pole resides in the right half-plane. Examples are provided to demonstrate calculating transfer functions from differential equations and analyzing stability based on pole locations.
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.
The document discusses phase plane analysis, a graphical method for studying second-order nonlinear systems. It describes phase portraits, singular points, limit cycles, and how to analyze linear and nonlinear systems using the phase plane. Phase plane analysis allows qualitative study of a nonlinear system's behavior from various initial conditions without analytical solutions. While restricted to second-order systems, it provides visualization of trajectories in the phase plane and applies to strong nonlinearities.
This document provides an overview of perturbation techniques for analyzing heat transfer problems. It discusses several objectives: to demonstrate the usefulness of perturbation techniques; to assist unfamiliar readers in understanding the techniques; and to show how the techniques are applied to specific problems. The document then reviews various perturbation methods - regular perturbation method, method of strained coordinates, method of matched asymptotic expansions, and method of extended perturbation series. It also discusses limitations and advantages of perturbation methods.
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.
A guide to the understanding of dynamic processes. Calculus of variations was the first step towards understanding the functioning of dynamic process that occur around us, be it the living world or man-made mechanisms.
The document discusses various transformations that can be applied to variables in SPSS to satisfy assumptions of normality, homogeneity of variance, and linearity. It describes logarithmic, square root, inverse, and square transformations and how to compute them in SPSS. Adjustments may need to be made to variable values depending on minimum/maximum values and distribution skew. The document provides examples of computing each transformation for a variable measuring time spent online.
The professor discusses how to convert performance specifications into desired regions for closed loop pole locations to ensure stability and meet specifications. He uses an example where the dominant closed loop dynamics are required to have a settling time below 4 seconds and a peak overshoot below 10%. By analyzing these specifications, he derives a region in the complex plane shaped like an open trapezoid. As long as the closed loop poles lie within this region, both the settling time and overshoot specifications will be met while also maintaining stability. Root locus analysis can then be used to determine controller parameters that place the closed loop poles within this desired region.
Introduction to perturbation theory, part-1Kiran Padhy
Perturbation theory provides an approximate method for solving quantum mechanical problems where the Hamiltonian cannot be solved exactly. It involves splitting the Hamiltonian into an exactly solvable unperturbed part (H0) and a perturbed part (H1) treated as a small disturbance. The eigenvalues and eigenstates of the full Hamiltonian are expressed as power series expansions in terms of the perturbation strength parameter λ, allowing the effects of the perturbation to be calculated order by order. There are two types of perturbation theory: time-independent, where the unperturbed eigenstates are stationary; and time-dependent, where they vary with time under the perturbation.
Equilibrium point analysis linearization techniqueTarun Gehlot
The document discusses the linearization technique for analyzing the behavior of solutions near equilibrium points of nonlinear systems of differential equations. It explains that nonlinear systems can be approximated by linearizing around equilibrium points using a Jacobian matrix. The eigenvalues of the Jacobian matrix then allow classifying the equilibrium point and predicting whether solutions will converge or diverge from it. This technique is demonstrated on examples, including the Van der Pol oscillator and pendulum equations.
Linearization involves developing a linear approximation of a nonlinear system around an operating point. This allows tools from linear systems theory to be applied to analyze and design controllers for nonlinear systems. Specifically, Taylor's theorem is used to expand the nonlinear functions as a linear combination of deviations from the operating point. The resulting linearized model is only valid locally but provides an approximate way to analyze system behavior if well-controlled near the operating point. Examples show how to derive linearized models for common nonlinear systems like tanks and chemical reactors.
This document discusses various quantitative analysis techniques for time series data, including regression analysis, trend models, seasonality models, autoregressive models, and techniques for addressing autocorrelation. It provides an overview of simple and multiple linear regression, assumptions of regression models, and methods for model specification testing including analysis of variance.
1. The document discusses frequency response analysis techniques, which analyze how a system responds to input signals of varying frequencies.
2. It describes two common frequency response techniques - Bode plots, which show magnitude and phase response as functions of frequency, and Nyquist plots, which plot magnitude against phase on a polar graph.
3. The techniques provide insights into system stability and dynamics and are useful for control system design, but their use requires complex derivations and they do not always directly indicate transient response characteristics.
This document discusses various heuristic search techniques, including generate-and-test, hill climbing, best first search, and simulated annealing. Generate-and-test involves generating possible solutions and testing them until a solution is found. Hill climbing iteratively improves the current state by moving in the direction of increased heuristic value until no better state can be found or a goal is reached. Best first search expands the most promising node first based on heuristic evaluation. Simulated annealing is based on hill climbing but allows moves to worse states probabilistically to escape local maxima.
Hill climbing algorithm in artificial intelligencesandeep54552
The hill climbing algorithm is a local search technique used to find the optimal solution to a problem. It works by starting with an initial solution and iteratively moving to a neighboring solution that has improved value until no better solutions can be found. Simple hill climbing only considers one neighbor at a time, while steepest ascent examines all neighbors and chooses the one closest to the optimal solution. The algorithm can get stuck at local optima rather than finding the global optimum. Techniques like simulated annealing incorporate randomness to help escape local optima.
This document discusses correlation, regression, and issues that can arise when performing regression analysis. It defines correlation and covariance, and how to interpret a scatter plot. It explains how to test for statistical significance of correlation and establish if a linear relationship exists between variables. Simple and multiple linear regression are explained, including assumptions, model construction, and importance of regression coefficients. It discusses how to assess the importance of independent variables in explaining the dependent variable using t-tests, F-tests, R-squared, and adjusted R-squared. Potential issues like heteroskedasticity and multicollinearity are also summarized.
The document provides a review of topics that will be covered on the final exam for a quantitative analysis for business course. The 3 hour exam will cover all topics discussed in the course and be worth 50% of the final grade. Key topics include linear regression, its assumptions, hypothesis testing of regression coefficients, and time series models such as moving averages, exponential smoothing, and decomposition. Multiple regression, adjusted R-squared, and seasonal variations with trend are also summarized.
Chapter 1 Introduction to Control Systems From the book (Ogata Modern Control Engineering 5th).
1-1 introduction to control systems.
1-2 examples of control systems.
1-3 open loop vs. close loop.
1-4 design and compensation of control systems.
The document discusses key concepts in Laplace transforms including:
1) The Laplace transform is defined as an integral transform that transforms a function of time into a function of a complex variable, simplifying analysis of differential equations.
2) Important properties include the Laplace transforms of derivatives and integrals, which allow transforming differential equations into algebraic equations.
3) The existence theorem guarantees a unique solution to initial value problems under certain conditions on the function.
This presentation gives complete idea about definitions of stability, BIBO, Absolute and relative stability, Routh-Hurwitz Criterion, Special Cases and numerical examples.
ME-314 Introduction to Control Engineering is a course taught to Mechanical Engineering senior undergrads. The course is taught by Dr. Bilal Siddiqui at DHA Suffa University. This lecture is about time response of systems derived by inspection of poles and zeros. Stability concepts and steady state errors are taught.
This formula book gives simple and useful formulas related to control system. It helps students in solving numerical problems, in their competitive examinations
This document provides an overview of transfer functions and stability analysis of linear time-invariant (LTI) systems. It discusses how the Laplace transform can be used to represent signals as algebraic functions and calculate transfer functions as the ratio of the Laplace transforms of the output and input. Poles and zeros are introduced as important factors for stability. A system is stable if all its poles reside in the left half of the s-plane and unstable if any pole resides in the right half-plane. Examples are provided to demonstrate calculating transfer functions from differential equations and analyzing stability based on pole locations.
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.
The document discusses phase plane analysis, a graphical method for studying second-order nonlinear systems. It describes phase portraits, singular points, limit cycles, and how to analyze linear and nonlinear systems using the phase plane. Phase plane analysis allows qualitative study of a nonlinear system's behavior from various initial conditions without analytical solutions. While restricted to second-order systems, it provides visualization of trajectories in the phase plane and applies to strong nonlinearities.
This document provides an overview of perturbation techniques for analyzing heat transfer problems. It discusses several objectives: to demonstrate the usefulness of perturbation techniques; to assist unfamiliar readers in understanding the techniques; and to show how the techniques are applied to specific problems. The document then reviews various perturbation methods - regular perturbation method, method of strained coordinates, method of matched asymptotic expansions, and method of extended perturbation series. It also discusses limitations and advantages of perturbation methods.
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.
A guide to the understanding of dynamic processes. Calculus of variations was the first step towards understanding the functioning of dynamic process that occur around us, be it the living world or man-made mechanisms.
The document discusses various transformations that can be applied to variables in SPSS to satisfy assumptions of normality, homogeneity of variance, and linearity. It describes logarithmic, square root, inverse, and square transformations and how to compute them in SPSS. Adjustments may need to be made to variable values depending on minimum/maximum values and distribution skew. The document provides examples of computing each transformation for a variable measuring time spent online.
The professor discusses how to convert performance specifications into desired regions for closed loop pole locations to ensure stability and meet specifications. He uses an example where the dominant closed loop dynamics are required to have a settling time below 4 seconds and a peak overshoot below 10%. By analyzing these specifications, he derives a region in the complex plane shaped like an open trapezoid. As long as the closed loop poles lie within this region, both the settling time and overshoot specifications will be met while also maintaining stability. Root locus analysis can then be used to determine controller parameters that place the closed loop poles within this desired region.
Introduction to perturbation theory, part-1Kiran Padhy
Perturbation theory provides an approximate method for solving quantum mechanical problems where the Hamiltonian cannot be solved exactly. It involves splitting the Hamiltonian into an exactly solvable unperturbed part (H0) and a perturbed part (H1) treated as a small disturbance. The eigenvalues and eigenstates of the full Hamiltonian are expressed as power series expansions in terms of the perturbation strength parameter λ, allowing the effects of the perturbation to be calculated order by order. There are two types of perturbation theory: time-independent, where the unperturbed eigenstates are stationary; and time-dependent, where they vary with time under the perturbation.
Equilibrium point analysis linearization techniqueTarun Gehlot
The document discusses the linearization technique for analyzing the behavior of solutions near equilibrium points of nonlinear systems of differential equations. It explains that nonlinear systems can be approximated by linearizing around equilibrium points using a Jacobian matrix. The eigenvalues of the Jacobian matrix then allow classifying the equilibrium point and predicting whether solutions will converge or diverge from it. This technique is demonstrated on examples, including the Van der Pol oscillator and pendulum equations.
Linearization involves developing a linear approximation of a nonlinear system around an operating point. This allows tools from linear systems theory to be applied to analyze and design controllers for nonlinear systems. Specifically, Taylor's theorem is used to expand the nonlinear functions as a linear combination of deviations from the operating point. The resulting linearized model is only valid locally but provides an approximate way to analyze system behavior if well-controlled near the operating point. Examples show how to derive linearized models for common nonlinear systems like tanks and chemical reactors.
This document discusses various quantitative analysis techniques for time series data, including regression analysis, trend models, seasonality models, autoregressive models, and techniques for addressing autocorrelation. It provides an overview of simple and multiple linear regression, assumptions of regression models, and methods for model specification testing including analysis of variance.
1. The document discusses frequency response analysis techniques, which analyze how a system responds to input signals of varying frequencies.
2. It describes two common frequency response techniques - Bode plots, which show magnitude and phase response as functions of frequency, and Nyquist plots, which plot magnitude against phase on a polar graph.
3. The techniques provide insights into system stability and dynamics and are useful for control system design, but their use requires complex derivations and they do not always directly indicate transient response characteristics.
This document discusses various heuristic search techniques, including generate-and-test, hill climbing, best first search, and simulated annealing. Generate-and-test involves generating possible solutions and testing them until a solution is found. Hill climbing iteratively improves the current state by moving in the direction of increased heuristic value until no better state can be found or a goal is reached. Best first search expands the most promising node first based on heuristic evaluation. Simulated annealing is based on hill climbing but allows moves to worse states probabilistically to escape local maxima.
Hill climbing algorithm in artificial intelligencesandeep54552
The hill climbing algorithm is a local search technique used to find the optimal solution to a problem. It works by starting with an initial solution and iteratively moving to a neighboring solution that has improved value until no better solutions can be found. Simple hill climbing only considers one neighbor at a time, while steepest ascent examines all neighbors and chooses the one closest to the optimal solution. The algorithm can get stuck at local optima rather than finding the global optimum. Techniques like simulated annealing incorporate randomness to help escape local optima.
This document discusses correlation, regression, and issues that can arise when performing regression analysis. It defines correlation and covariance, and how to interpret a scatter plot. It explains how to test for statistical significance of correlation and establish if a linear relationship exists between variables. Simple and multiple linear regression are explained, including assumptions, model construction, and importance of regression coefficients. It discusses how to assess the importance of independent variables in explaining the dependent variable using t-tests, F-tests, R-squared, and adjusted R-squared. Potential issues like heteroskedasticity and multicollinearity are also summarized.
The document provides a review of topics that will be covered on the final exam for a quantitative analysis for business course. The 3 hour exam will cover all topics discussed in the course and be worth 50% of the final grade. Key topics include linear regression, its assumptions, hypothesis testing of regression coefficients, and time series models such as moving averages, exponential smoothing, and decomposition. Multiple regression, adjusted R-squared, and seasonal variations with trend are also summarized.
Chapter 1 Introduction to Control Systems From the book (Ogata Modern Control Engineering 5th).
1-1 introduction to control systems.
1-2 examples of control systems.
1-3 open loop vs. close loop.
1-4 design and compensation of control systems.
The document discusses key concepts in Laplace transforms including:
1) The Laplace transform is defined as an integral transform that transforms a function of time into a function of a complex variable, simplifying analysis of differential equations.
2) Important properties include the Laplace transforms of derivatives and integrals, which allow transforming differential equations into algebraic equations.
3) The existence theorem guarantees a unique solution to initial value problems under certain conditions on the function.
This presentation gives complete idea about definitions of stability, BIBO, Absolute and relative stability, Routh-Hurwitz Criterion, Special Cases and numerical examples.
ME-314 Introduction to Control Engineering is a course taught to Mechanical Engineering senior undergrads. The course is taught by Dr. Bilal Siddiqui at DHA Suffa University. This lecture is about time response of systems derived by inspection of poles and zeros. Stability concepts and steady state errors are taught.
This formula book gives simple and useful formulas related to control system. It helps students in solving numerical problems, in their competitive examinations
The document discusses stability in linear control systems. It defines three types of stability: absolutely stable, conditionally stable, and marginally stable. A system is stable if its output remains bounded over time, unstable if output grows without bound, and marginally stable if output remains constant or oscillates. The Routh-Hurwitz criterion provides a necessary and sufficient condition for stability - a stable system has all characteristic polynomial coefficients and first Routh array column elements positive. Special cases in the Routh array are addressed.
Stability criteria and Analysis_Control Systems Engineering_MEB 4101.pdfMUST
This document provides an overview of stability criteria and analysis for control systems engineering. It discusses topics like transfer functions, poles and zeros, stability definitions, Routh-Hurwitz stability criterion, and using the Routh array to analyze system stability based on the characteristic equation. Examples are provided to demonstrate identifying poles and zeros, checking if systems satisfy necessary stability conditions, and using the Routh table to determine stability.
This document provides information on open loop control systems and transfer functions. It defines open loop systems as those without feedback, and provides examples of a toaster and washing machine. Key aspects covered include the advantages and disadvantages of open loop systems, defining the transfer function as the output over input in the Laplace domain, and discussing poles, zeros and stability. Poles and zeros are defined as the roots of the denominator and numerator, respectively. The document discusses plotting poles and zeros on the s-plane and using this to determine system stability. Matlab code examples are provided to calculate and visualize poles, zeros and step responses for different transfer functions.
This document provides information about open loop control systems and transfer functions. It defines open loop control systems as systems without feedback, and provides examples of open loop systems like a toaster and washing machine. It then discusses transfer functions, which are defined as the ratio of the Laplace transform of the output to the input. Poles and zeros are also defined, with poles making the transfer function infinite and zeros making it zero. The document notes that stability depends on all poles being in the left half of the s-plane. It provides examples of pole-zero plots and coding in MATLAB to analyze transfer functions.
LECTURE 4. Stability criteria and Analysis_Control Systems Engineering_MEB 41...MUST
This document discusses stability criteria and analysis for control systems engineering. It covers topics like transfer functions, poles and zeros, stability definitions, and the Routh-Hurwitz stability criterion. The Routh-Hurwitz criterion provides a systematic way to determine if a system is stable by constructing an array from the coefficients of the characteristic equation and checking that the first column entries are all positive. The document provides examples of analyzing stability for different characteristic equations using these concepts.
This document discusses observer-based control system design. It introduces full order and reduced order state observers, which estimate all or some unmeasurable state variables, respectively. The full order state observer design problem is shown to be mathematically equivalent to the pole placement problem. This "duality property" allows solving the observer design problem using pole placement techniques for the dual system. Methods for determining the observer gain matrix K include using a transformation matrix P, direct substitution, and Ackermann's formula. The observer poles should be placed faster than the controller poles for accurate state estimation. An example designs a full order observer for a given system to achieve desired closed loop poles.
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
Chapter 6 Control systems analysis and design by the root-locus method. From the book (Ogata Modern Control Engineering 5th).
6-1 introduction.
6-2 Root locus plots.
6-5 root locus approach to control-system design.
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.
Analysis and Design of Control System using Root LocusSiyum Tsega Balcha
Root locus analysis is a powerful tool in control systems engineering used to analyze the behavior of a system's closed-loop poles as a function of a parameter, typically a controller gain. It provides engineers with valuable insights into how changing system parameters affect stability and performance, helping them design robust and stable control systems. Let's explore the key concepts, techniques, and practical implications of root locus analysis. At its core, root locus analysis focuses on the movement of the closed-loop poles in the complex plane as a control parameter varies. These poles represent the characteristic equation's roots, which determine the system's stability and transient response. By examining the pole locations as the parameter changes, engineers can gain a deeper understanding of the system's behavior and make informed design decisions.
THIS PPT IS ABOUT THE ANALYZE THE STABILITY OF DC SERVO MOTOR USING NYQUIST PLOT AND IN THIS PPT WE CAN ALSO SEE THE DIFFERENT CHARACTERISTICS EQUATION FOR THE DC SERVO MOTOR AND THE EXAMPLE GRAPHS ARE ALSO SHOWN IN THIS PPT AND THIS PPT IS SO USEFUL FOR THE CONTROL SYSTEM STUDENTS AND ANALYSIS OF THE EQUATIONS ARE ALSO AVAILABLE IN THIS PPT
This document discusses stability analysis in linear control systems. It defines stability as a system's ability to return to equilibrium after a disturbance or remain bounded for a bounded input. The stability of a closed-loop system can be determined by examining the location of its closed-loop poles in the s-plane - if any poles lie in the right half plane, the system is unstable. The Routh-Hurwitz stability criterion provides a test to determine if all poles lie in the left half plane using the signs of coefficients in an array formed from the characteristic equation.
Transient and Steady State Response - Control Systems EngineeringSiyum Tsega Balcha
. Two crucial aspects of this behavior are transient and steady-state responses. These concepts encapsulate how a system behaves over time, from the moment an input is applied to when the system settles into a stable state. The transient response of a system characterizes its behavior during the initial phase after a change in input. It reflects how the system reacts as it transitions from one state to another. This phase is marked by dynamic changes in the system's output as it adjusts to the new conditions imposed by the input.
Characteristics of Transient Response are Time Constant, overshoot, settling time and damping.
Once the transient effects have subsided, the system enters the steady-state, where its behavior becomes constant over time. In this phase, the system operates under stable conditions, and its output remains within a narrow range around the desired value, despite fluctuations in input or external disturbances. Characteristics of Steady-State Response are Steady-State Error, stability, accuracy, robustness,.
This document introduces the root locus technique for analyzing how the closed-loop poles of a control system vary with changes in the controller gain. It provides 5 rules for constructing a root locus diagram:
1) Locate open-loop poles and zeros.
2) The number of root locus branches equals the greater of open-loop poles or zeros.
3) Points on the real axis are on the locus if open-loop poles/zeros to the right are odd.
4) Asymptotes radiate from the centroid at fixed angles depending on open-loop poles/zeros.
5) Branches depart breakaway points where multiple roots occur at angles of ±180/n degrees.
The document discusses stability analysis of linear time-invariant systems. It defines stability, instability, and marginal stability. A stable system is one where the natural response approaches zero over time. An unstable system's natural response grows without bound over time. A marginally stable system's natural response remains constant or oscillates over time.
The Routh-Hurwitz criterion is introduced as a method to determine stability without calculating system poles directly. It involves generating a Routh table from the characteristic equation and interpreting the table to determine the number of poles in each part of the s-plane - the left half-plane, right half-plane, or the jω-axis. If the Routh table has any sign changes in
The document discusses mathematical modeling of physical control systems. It begins by explaining that the first step is to develop a linear mathematical model around an operating point to analyze the system. It then discusses different types of physical variables and components that can be modeled, including electrical, mechanical, thermal and fluidic devices. Differential equations relating inputs and outputs are obtained using physics laws. The document also covers modeling translational and rotational mechanical systems using elements like mass, spring and damper. It discusses different variable types, analogies, transfer functions and block diagram representation of systems. It provides examples of reducing complex block diagrams to obtain closed loop transfer functions.
Tocci chapter 13 applications of programmable logic devices extendedcairo university
The document discusses the family tree of digital systems, including standard logic, ASICs, microprocessors, DSPs, and different types of programmable logic devices like PLDs, CPLDs, and FPGAs. It covers the architectures of early PLDs like PROM, PAL, and FPLA, which have programmable AND and OR gates, as well as the different programming technologies for modern PLDs like SRAM, flash memory, EPROM, and antifuse.
The document discusses various types of memory devices and technologies. It covers topics like memory terminology, ROM, EPROM, EEPROM, and flash memory. Key points include that ROM is read-only memory that can be mask-programmed or one-time programmable, while EPROM, EEPROM and flash memory use floating-gate MOS transistors and can be electrically erased and reprogrammed in bulk or individually.
This document covers MSI (medium-scale integration) logic circuits. It discusses decoders, multiplexers, encoders, and other digital logic components. Decoders take binary inputs and activate one of multiple outputs. Multiplexers select one of several inputs to output based on a digital select code. Encoders convert coded inputs to binary outputs. The document provides circuit diagrams and explanations of common MSI components like decoders, multiplexers, priority encoders, and code converters. It also discusses applications such as seven-segment displays, LCDs, and digital systems.
This document discusses various types of counters and registers, including asynchronous (ripple) counters, synchronous (parallel) counters, decade counters, BCD counters, shift registers, ring counters, and Johnson counters. It provides details on their structure, operation, and applications. Key topics covered include propagation delay in ripple counters, the advantages of synchronous counters, designing counters with different mod numbers, decoding counter states, and using counters for functions like stepper motor control.
Tocci ch 6 digital arithmetic operations and circuitscairo university
The document discusses digital arithmetic operations and circuits, including binary addition, representing signed numbers, addition and subtraction in the two's complement system, multiplication and division of binary numbers, BCD addition, hexadecimal arithmetic, and arithmetic circuits. It describes how an ALU performs arithmetic operations by accepting data from memory and executing instructions from the control unit, using adders, registers, and control signals to perform addition and subtraction.
Tocci ch 3 5 boolean algebra, logic gates, combinational circuits, f fs, - re...cairo university
This document contains lecture slides on logic gates and Boolean algebra. It covers topics like De Morgan's theorem, sum of products and product of sums, logic gate representations including NAND and NOR gates, flip flops including JK and D flip flops. Circuit diagrams and truth tables are provided for latching circuits and different types of flip flops. The document is copyrighted and appears to be from a course on logic gates and Boolean algebra taught by Muhammad A M Islam.
The document discusses latches and flip-flops, basic memory circuits. It describes the latch, SR flip-flop, CMOS enabled SR flip-flop, and CMOS SRAM memory cell. It also discusses a one-transistor dynamic RAM cell. The document focuses on the circuit designs and operations of various basic memory components.
A14 sedra ch 14 advanced mos and bipolar logic circuitscairo university
This document discusses advanced logic circuits including pseudo-NMOS logic, pass-transistor logic, dynamic MOS logic, emitter-coupled logic (ECL), and BiCMOS digital circuits. Pseudo-NMOS logic uses one transistor per input instead of two to reduce area and delay. Pass-transistor logic builds logic functions using NMOS or transmission gate switches. Dynamic MOS logic uses precharge and evaluate phases to reduce static power at the cost of increased sensitivity to noise. ECL uses differential pairs for noise immunity and constant current sources. BiCMOS combines CMOS and BJTs to achieve high performance with lower power than ECL.
This document discusses CMOS digital logic circuits. It covers special characteristics like fan-out, power dissipation, and propagation delay. It then describes the basic CMOS inverter circuit. The inverter uses complementary NMOS and PMOS transistors for the pull-down and pull-up networks. When the input is low, the NMOS transistor is on and the PMOS is off, pulling the output high. When the input is high, the opposite occurs. This allows the output to switch between 0V and the supply voltage with very low static power dissipation.
The document discusses the high-frequency response of common-emitter (CE) amplifiers. It first examines the CE amplifier circuit and its mid-band behavior when the capacitors are short circuits. It then explores how each internal capacitor (CB, CC, CE) affects the frequency response as it blocks signal flow at lower frequencies. The document also considers the Miller effect, which multiplies the input capacitance seen at the base due to feedback through the amplifier. Overall, the internal capacitances lower the amplifier's bandwidth as frequency decreases.
This document describes the structure and operation of MOS field-effect transistors (MOSFETs). It covers topics such as device structure, current-voltage characteristics, MOSFET circuits at DC, and large-signal equivalent circuit models. Examples are provided to illustrate how to analyze MOSFET circuits and calculate current and voltage values. The document also discusses the physical mechanisms involved in MOSFET operation such as creation of a channel for current flow and derivation of current-voltage relationships.
This document discusses MOS field-effect transistors (MOSFETs) and includes the following topics:
1. It outlines the structure and operation of MOSFET devices, including creating a channel for current flow and deriving the iD-vDS relationship.
2. It covers current-voltage characteristics of MOSFETs such as the iD-vDS, iD-vGS curves and their different operating regions.
3. It provides examples of solving for unknown variables in MOSFET circuits operating in different regions, such as the triode and saturation regions.
This document discusses MOS field-effect transistors (MOSFETs) and their operation. It covers MOSFET device structure and physical operation, current-voltage characteristics, MOSFET circuits at DC, applying MOSFETs in amplifier design, small signal operations and models, and other related topics. The document contains diagrams and equations to illustrate MOSFET characteristics and circuit analysis. It provides an overview of the key concepts and applications of MOSFET devices.
This document discusses coordinate systems and vector calculus concepts needed for electromagnetic field theory. It introduces Cartesian, cylindrical, and spherical coordinate systems. It explains that vector integration requires defining appropriate differential elements (length, area, volume) that vary based on the coordinate system. It also introduces concepts of gradient, divergence, and curl - vector operators used to take derivatives of vector fields. The gradient represents the maximum rate of change, divergence measures flux, and curl represents rotational nature. Expressions for these operators are given in the three coordinate systems.
The document discusses the interaction of electromagnetic fields (EMFs) with biological systems. It notes that the topic is studied to assess potential health hazards, enable applications in biology and medicine, and optimize the design of EM devices. The document outlines various effects of EMF exposure at different frequencies, therapeutic and diagnostic EMF applications, and the need to model human exposure and effects through governing equations and human body models. Key areas covered include dosimetry, various human body models, RF applications like keyless entry and MRI, hyperthermia modeling, and diagnostic applications such as endoscopic capsules.
1. The document discusses various electromagnetic boundary conditions including:
- Electric and magnetic field boundary conditions between dielectric-dielectric interfaces where the normal component of B and tangential component of E are continuous.
- Conductor-dielectric boundary conditions where the surface charge density is related to the normal electric field component.
2. Faraday's law relates the rate of change of magnetic flux through a loop to the induced electromotive force around the loop. Lenz's law states that the induced current will flow such that it creates a magnetic field opposing the original change in flux.
3. The plane wave solution for electromagnetic waves in free space represents the electric and magnetic fields as propagating sinusoidal functions of space and time with
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Here are some examples of FDA-approved therapeutic devices that use direct current (DC) electric fields:
- Bone growth stimulators - Use pulsed electromagnetic fields or capacitively coupled electric fields to promote bone healing of fractures that are not healing on their own.
- Transcutaneous electrical nerve stimulators (TENS) - Apply electric currents to stimulate nerves for pain relief and muscle rehabilitation.
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The document provides an overview of the Silicon Labs C8051F020 microcontroller. It describes the microcontroller's CPU, memory organization, I/O ports, analog and digital peripherals such as ADCs, DACs, and comparators. It also discusses the microcontroller's special function registers used to control and interface with its various peripherals.
Lecture 1 (course overview and 8051 architecture) rv01cairo university
This document provides an overview and syllabus for a course on the 8051 microcontroller architecture. The course covers the 8051 architecture, instruction set, programming using assembly and C languages, peripherals, interrupts, timers, serial communication, analog-to-digital converters, and more. The goals are for students to understand the 8051 architecture, develop skills in programming 8051 microcontrollers using different languages, and interface the microcontroller to external components. The course consists of lectures, tutorials, and labs using the Silicon Labs C8051F020 development board.
Redefining brain tumor segmentation: a cutting-edge convolutional neural netw...IJECEIAES
Medical image analysis has witnessed significant advancements with deep learning techniques. In the domain of brain tumor segmentation, the ability to
precisely delineate tumor boundaries from magnetic resonance imaging (MRI)
scans holds profound implications for diagnosis. This study presents an ensemble convolutional neural network (CNN) with transfer learning, integrating
the state-of-the-art Deeplabv3+ architecture with the ResNet18 backbone. The
model is rigorously trained and evaluated, exhibiting remarkable performance
metrics, including an impressive global accuracy of 99.286%, a high-class accuracy of 82.191%, a mean intersection over union (IoU) of 79.900%, a weighted
IoU of 98.620%, and a Boundary F1 (BF) score of 83.303%. Notably, a detailed comparative analysis with existing methods showcases the superiority of
our proposed model. These findings underscore the model’s competence in precise brain tumor localization, underscoring its potential to revolutionize medical
image analysis and enhance healthcare outcomes. This research paves the way
for future exploration and optimization of advanced CNN models in medical
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ACEP Magazine edition 4th launched on 05.06.2024Rahul
This document provides information about the third edition of the magazine "Sthapatya" published by the Association of Civil Engineers (Practicing) Aurangabad. It includes messages from current and past presidents of ACEP, memories and photos from past ACEP events, information on life time achievement awards given by ACEP, and a technical article on concrete maintenance, repairs and strengthening. The document highlights activities of ACEP and provides a technical educational article for members.
Using recycled concrete aggregates (RCA) for pavements is crucial to achieving sustainability. Implementing RCA for new pavement can minimize carbon footprint, conserve natural resources, reduce harmful emissions, and lower life cycle costs. Compared to natural aggregate (NA), RCA pavement has fewer comprehensive studies and sustainability assessments.
TIME DIVISION MULTIPLEXING TECHNIQUE FOR COMMUNICATION SYSTEMHODECEDSIET
Time Division Multiplexing (TDM) is a method of transmitting multiple signals over a single communication channel by dividing the signal into many segments, each having a very short duration of time. These time slots are then allocated to different data streams, allowing multiple signals to share the same transmission medium efficiently. TDM is widely used in telecommunications and data communication systems.
### How TDM Works
1. **Time Slots Allocation**: The core principle of TDM is to assign distinct time slots to each signal. During each time slot, the respective signal is transmitted, and then the process repeats cyclically. For example, if there are four signals to be transmitted, the TDM cycle will divide time into four slots, each assigned to one signal.
2. **Synchronization**: Synchronization is crucial in TDM systems to ensure that the signals are correctly aligned with their respective time slots. Both the transmitter and receiver must be synchronized to avoid any overlap or loss of data. This synchronization is typically maintained by a clock signal that ensures time slots are accurately aligned.
3. **Frame Structure**: TDM data is organized into frames, where each frame consists of a set of time slots. Each frame is repeated at regular intervals, ensuring continuous transmission of data streams. The frame structure helps in managing the data streams and maintaining the synchronization between the transmitter and receiver.
4. **Multiplexer and Demultiplexer**: At the transmitting end, a multiplexer combines multiple input signals into a single composite signal by assigning each signal to a specific time slot. At the receiving end, a demultiplexer separates the composite signal back into individual signals based on their respective time slots.
### Types of TDM
1. **Synchronous TDM**: In synchronous TDM, time slots are pre-assigned to each signal, regardless of whether the signal has data to transmit or not. This can lead to inefficiencies if some time slots remain empty due to the absence of data.
2. **Asynchronous TDM (or Statistical TDM)**: Asynchronous TDM addresses the inefficiencies of synchronous TDM by allocating time slots dynamically based on the presence of data. Time slots are assigned only when there is data to transmit, which optimizes the use of the communication channel.
### Applications of TDM
- **Telecommunications**: TDM is extensively used in telecommunication systems, such as in T1 and E1 lines, where multiple telephone calls are transmitted over a single line by assigning each call to a specific time slot.
- **Digital Audio and Video Broadcasting**: TDM is used in broadcasting systems to transmit multiple audio or video streams over a single channel, ensuring efficient use of bandwidth.
- **Computer Networks**: TDM is used in network protocols and systems to manage the transmission of data from multiple sources over a single network medium.
### Advantages of TDM
- **Efficient Use of Bandwidth**: TDM all
CHINA’S GEO-ECONOMIC OUTREACH IN CENTRAL ASIAN COUNTRIES AND FUTURE PROSPECTjpsjournal1
The rivalry between prominent international actors for dominance over Central Asia's hydrocarbon
reserves and the ancient silk trade route, along with China's diplomatic endeavours in the area, has been
referred to as the "New Great Game." This research centres on the power struggle, considering
geopolitical, geostrategic, and geoeconomic variables. Topics including trade, political hegemony, oil
politics, and conventional and nontraditional security are all explored and explained by the researcher.
Using Mackinder's Heartland, Spykman Rimland, and Hegemonic Stability theories, examines China's role
in Central Asia. This study adheres to the empirical epistemological method and has taken care of
objectivity. This study analyze primary and secondary research documents critically to elaborate role of
china’s geo economic outreach in central Asian countries and its future prospect. China is thriving in trade,
pipeline politics, and winning states, according to this study, thanks to important instruments like the
Shanghai Cooperation Organisation and the Belt and Road Economic Initiative. According to this study,
China is seeing significant success in commerce, pipeline politics, and gaining influence on other
governments. This success may be attributed to the effective utilisation of key tools such as the Shanghai
Cooperation Organisation and the Belt and Road Economic Initiative.
3. Absolute Stability
• The most important characteristic of the dynamic
behavior of a control system is absolute stability.
• A control system is in equilibrium if, in the absence
of any disturbance or input, the output stays in the
same state.
• A linear time-invariant control system is stable if the
output eventually comes back to its equilibrium
state when the system is ONLY subjected to an
initial condition.
4. Absolute Stability
• A linear time-invariant (LTI) control system is
critically stable if oscillations of the output continue
forever.
• It is unstable if the output diverges without bound
from its equilibrium state when the system is
subjected to an initial condition.
• Thus, a LTI is stable, if it is a bounded-input-
bounded-output (BIBO) system.
5. Relative Stability
• An important system behavior (other than absolute
stability) to which we must give careful
consideration includes relative stability.
• Since a physical control system involves energy
storage, the output of the system, when subjected
to an input, cannot follow the input immediately
but exhibits a transient response before a steady
state can be reached.
• The duration of that transient response in the
practical sense is a measure of relative stability.
6. Time &
Frequency
Domain Stability
Analysis
Linear Time Invariant
System
(Frequency domain)
Complex Frequency
Domain
(Routh stability
analysis)
Real Frequency
Domain
(Nyquist stability
analysis)
Time-varying &
Nonlinear System
(Time domain)
Time Domain
Analysis
(Lyapunov stability
analysis)
7. Routh’s Stability Criterion
• The Routh’s stability criterion tells us whether or
not there are unstable roots in a polynomial
equation without actually solving for them.
• This stability criterion applies to polynomials with
only a finite number of terms.
• When the criterion is applied to a control system,
information about absolute stability can be
obtained directly from the coefficients of the
characteristic equation.
8. Routh’s Stability Analysis Procedure
• Write the polynomial in s in the following form:
where the coefficients are real quantities.
We assume that an an > 0; that is, any zero
root has been removed.
If any of the coefficients are zero or negative in the
presence of at least one positive coefficient,
a root or roots exist that are imaginary or that have
positive real parts.
Therefore, in such a case, the system is not stable.
9. Routh’s Stability Analysis Procedure
• If we are interested in only the absolute stability,
there is no need to follow the procedure further.
Note that all the coefficients must be positive.
10. Routh’s Stability Analysis Procedure
• If all coefficients are positive, arrange the coefficients of the
polynomial in rows and columns according to the following
pattern:
11. Routh’s Stability Analysis Procedure
• The process of forming rows continues until we run out of
elements. (The total number of rows is n+1). The
coefficients b1, b2, b3 , and so on, are evaluated as follows:
12. Routh’s Stability Analysis Procedure
• The evaluation of the b’s is continued until the remaining
ones are all zero.
• The same cross-multiplication pattern is followed in
evaluating the c’s, d’s, e’s, and so on. That is,
13. Routh’s Stability Analysis Procedure
This process is continued until the nth row has been
completed.
The complete array of coefficients is quasi-triangular.
In developing the array an entire row may be divided or
multiplied by a positive number in order to simplify the
subsequent numerical calculation without altering the
stability conclusion.
14. Implication of Routh’s Stability
Criterion
• Routh’s stability criterion states that the number of
roots of the characteristic equation with positive
real parts is equal to the number of changes in sign
of the coefficients of the first column of the array.
• The necessary and sufficient condition that all roots
of the characteristic equation lie in the left-half s-
plane is that all the coefficients of the characteristic
equation be positive and all terms in the first
column of the array have positive signs.
15. Example 5–11 – p. 214 – Ogata V
• Apply Routh’s stability criterion to the following
third-order polynomial:
• where all the coefficients are positive numbers.
17. Example 5–12 – p. 214 – Ogata V
• Consider the following polynomial:
Solution
The first two rows can be obtained directly from the
given polynomial.
The second row can be divided by 2
18. Solution
• Having done so we get
𝑠3
1 2 0
We proceed with the remainder of the array as follows
The number of changes in sign of the coefficients in the
first column is 2.
This means that there are two roots with positive real
parts.
19. Special Cases
• If a first-column term in any row is zero, but the
remaining terms are not zero or there is no
remaining term, then the zero term is replaced by a
very small positive number ε and the rest of the
array is evaluated.
20. Example
• Consider the following equation:
The array of coefficients is
Now that the sign of the coefficient above the zero (ε) is
the same as that below it, it indicates that there are a pair
of imaginary roots (in that case at s = ±j).
21. Special Cases (Contd.)
• If, however, the sign of the coefficient above the
zero (ε) is opposite that below it, it indicates that
there are two sign changes of the coefficients in the
first column.
• In that case there are two coincident roots in the
right-half s-plane.
22. Relative Stability Analysis
• Routh’s stability criterion provides the answer to
• the question of absolute stability.
• This, in many practical cases, is not sufficient.
• We usually require information about the relative
stability of the system.
• A useful approach for examining relative stability is to
shift the s-plane axis and apply Routh’s stability
criterion.
• That is, we substitute
𝑠 = 𝑠−σ
23. Relative Stability Analysis
• into the characteristic equation of the system, write
the polynomial in terms of 𝑠 andapply Routh’s
stability criterion to the new polynomial in 𝑠
• The number of changes of sign in the first column of
the array developed for the polynomial in 𝑠 is equal
to the number of roots that are located to the right
of the vertical line s = –σ.
• Thus, this test reveals the number of roots that lie
to the right of the vertical line s = –σ.
24. Application of Routh’s Stability Criterion
to Control-System Analysis
• It is possible to determine the effects of changing
one or two parameters of a system by examining
the values that cause instability, particularly by
determining the stability range of one (or more)
parameter value.
25. Example
• Determine the range of K for stability for the system
shown.
Solution
The closed-loop transfer function is
26. Example (Contd.)
• The characteristic equation is
Routh’s array becomes
For stability, K must be positive, and all coefficients in
the first column must be positive. Therefore,
28. Introduction
• The basic characteristic of the transient response of a closed-loop
system is closely related to the location of the closed-loop poles.
• If the system has a variable loop gain, then the location of the
closed-loop poles depends on the value of the loop gain chosen.
• It is important, therefore, that the designer know how the closed-
loop poles move in the s plane as the loop gain is varied.
• From the design viewpoint, in some systems simple gain
adjustment may move the closed-loop poles to desired locations.
• If the gain adjustment alone does not yield a desired result,
addition of a compensator to the system will become necessary.
• The closed-loop poles are the roots of the characteristic equation.
29. The Concept
• The root-locus method is one in which the roots of the
characteristic equation are plotted for all values of a
system parameter, which will be assumed to be the
gain of the open-loop transfer function, unless
otherwise stated.
• The roots corresponding to a particular value of this
parameter can then be located on the resulting graph.
• It is desired that the designer have a good
understanding of the method for generating the root
loci of the closed-loop system, both by hand and by use
of a computer software program like MATLAB.
30. Angle and Magnitude Conditions
• For the negative feedback system shown the closed-loop transfer
function is
The characteristic equation for this closed-loop system is
or
Here we assume that G(s)H(s) is a rational polynomial in s.
31. Angle and Magnitude Conditions
• Since G(s)H(s) is a complex quantity, the characteristic can be split
into two equations by equating the angles and magnitudes of both
sides, respectively, to obtain
32. Angle and Magnitude Conditions
• The values of s that fulfill both the angle and
magnitude conditions are the roots of the
characteristic equation, or the closed-loop poles.
• A locus of the points in the complex plane satisfying
the angle condition alone is the root locus.
• The roots of the characteristic equation (the closed-
loop poles) corresponding to a given value of the
gain can be determined from the magnitude
condition.
33. The General Implication
• Generally, G(s)H(s) involves a gain parameter K, and the characteristic
equation may be written as
Then the root loci for the system are the loci of the closed-loop poles
as the gain K is varied from 0 to ∞.
The angles of the complex quantities originating from the open-loop
poles and open-loop zeros to a test point s are measured in the
counterclockwise direction.
In order that a test point lie on (i.e., be part of) the root locus, it
must satisfy the angle and magnitude conditions.
34. The General Implication
• For example, if G(s)H(s) is given by
where –p2 and –p3 are complex-conjugate poles, then the angle
of G(s)H(s) is
where 𝜙1 , θ1 , θ2 , θ3 , and θ4 are measured counterclockwise.
The magnitude of G(s)H(s) for this system is
where A1, A2, A3, A4, and B1 are the magnitudes of the complex
quantities s+p1, s+p2, s+p3, s+p4, and s+z1, respectively.
35. The General Implication
Diagram showing angle and magnitude measurements from open-loop poles and
open-loop zero to test point s.
36. Very Important
• Because the open-loop complex-conjugate poles and complex-
conjugate zeros, if any, are always located symmetrically about the
real axis, the root loci are always symmetrical w.r.t. this axis.
• Therefore, we only need to construct the upper half of the root loci
and draw the mirror image of the upper half in the lower-half s plane.
• Because graphical measurements of angles and magnitudes are
involved in the analysis, we find it necessary to use the same
divisions on the abscissa as on the ordinate axis when sketching the
root locus on graph paper.
• The number of individual root loci for a system is the same as the
number of open-loop poles.
• The starting points of the root loci (the points corresponding to K = 0)
are open-loop poles.
37. Example 6–1 – p. 273 – Ogata V
• Consider the negative feedback system given by:
1. Sketch the root-locus plot
2. Determine the value of K such that the damping ratio of the pair
of dominant complex-conjugate closed-loop poles is 0.5.
Solution
For the given system, the angle condition becomes
38. Example 6–1 – p. 273 – Ogata V
• The magnitude condition is
Computational Steps
1. Determine the root loci on the real axis.
To determine the root loci on the real axis, we select a test point, s.
a) If s > 0, then:
(angle condition not satisfied)
b) If 0 > s > -1, then:
Thus
(angle condition satisfied)
39. Example 6–1 – p. 273 – Ogata V
c) If -1 > s > -2, then:
Thus
(angle condition not satisfied)
d) If -2 > s > -∞, then:
= 180°
Thus
-540° (angle condition satisfied)
Thus, the portion of the real axis that lies on the root locus is given by:
]0,1[]2,[ S
40. Example 6–1 – p. 273 – Ogata V
2. Determine the asymptotes of the root loci.
The asymptotes of the root loci as s approaches infinity must lie on the real axis.
This is because the root loci are symmetrical about the real axis.
They can be determined as follows:
a) Number of asymptotes = n – m,
where n = number of poles & m = number of zeros.
In our case n = 3 & m = 0, so there are three asymptotes.
b) The angles of the asymptotes are given by:
,
12180
mn
k
k
k = 0, 1, 2, . . ., n - m
In our case the angles are given by θo = 60°, θ1 = 180°, θ2 = 300°,
And the asymptotes with the three negative angles coincide with the other
three.
41. Example 6–1 – p. 273 – Ogata V
c) The point where they intersect the real axis is given by:
mn
zp
n
i
m
j
ji
A
1 1
In our case
1
3
0210
A
The three asymptotes
42. Example 6–1 – p. 273 – Ogata V
3. Determine the breakaway point.
To plot root loci accurately, we must find the breakaway point, where the root-locus
branches originating from the poles break away from the real axis and move into the
complex plane, as K is increased.
The breakaway point corresponds to a point in the s plane where multiple roots of
the characteristic equation occur.
To find the breakaway point let us write the characteristic equation as
where A(s) and B(s) do not contain K.
f(s) = 0 has multiple roots at points where
Proof
Suppose that f(s) has multiple roots of order r, where r ≥ 2.
Then f(s) may be written as
43. Example 6–1 – p. 273 – Ogata V
121
31
2
1
1
...
......
...
)(
n
r
n
r
n
r
ssssss
ssssss
ssssssr
ds
sdf
0
)(
1
ssds
sdf
Now
where
44. Example 6–1 – p. 273 – Ogata V
The particular value of K that will yield multiple roots of the characteristic equation
is obtained from
Thus
or
0)(')()(')()(')()(')( sKAsAsAsBsBsAsAsB
0)()( sKAsB
Thus
45. Example 6–1 – p. 273 – Ogata V
Next we have
= 0
This confirms that the breakaway points can be simply determined from the roots of
If a point at which dK/ds = 0 is on a root locus, it is an actual breakaway or break-
in point. Otherwise, it is not.
In our case the characteristic equation G(s) + 1 = 0 is given by
or
so
46. Example 6–1 – p. 273 – Ogata V
The two roots are given by
Since the breakaway point must lie on a root locus between 0 and –1, it is clear
that s = –0.4226 corresponds to the actual breakaway point. Point s = –1.5774 is not
on the root locus. Hence, this point is not an actual breakaway or break-in point.
In fact
4. Determine the points where the root loci cross the imaginary axis.
let s = jω in the characteristic equation, equate both the real part and the imaginary
part to zero, and then solve for ω and K. For the present system, the characteristic
equation, with s = jω, is
or
47. Example 6–1 – p. 273 – Ogata V
Equating both the real and imaginary parts of this last equation to zero, respectively,
we obtain
from which
Thus, root loci cross the imaginary axis at 𝜔 = ± 2 and the value of K at the
crossing points is 6.
Also, a root-locus branch on the real axis touches the imaginary axis at ω = 0.
The value of K is zero at this point.
48. Example 6–1 – p. 273 – Ogata V
5. Sketch the root loci.
Asymptote
Asymptote
49. Example 6–1 – p. 273 – Ogata V
6. Determine the point on the root locus where the damping ration of the
dominant poles is 0.5.
Closed-loop poles with ζ = 0.5 lie on lines passing through the origin and making
angles with the negative real axis given by ±cos-1 ζ = ±cos-1 0.5 = ±60° with the
negative real axis.
From the previous slide such closed loop poles are approximately given by
s = -0.33 ± j 0.58 complex rad/s
The value of K that yields such poles is found from the magnitude condition as
follows:
𝐾 = 𝑠 𝑠 + 1 𝑠 + 2 𝑠=−0.33+𝑗0.58 ≈ 1.05
The basic construction can be found on the next slide.
51. Example 6–2 – p. 279 – Ogata V
• Consider the negative feedback system shown
Solution
For this system
K ≥ 0
G(s) has a pair of complex-conjugate poles at
52. Example 6–2 – p. 279 – Ogata V
Computational Steps
1. Determine the root loci on the real axis.
For any test point s on the real axis, the sum of the angular contributions of the
complex-conjugate poles is 360°, as shown
Thus the net effect of the complex-conjugate poles is zero on the real axis.
53. Example 6–2 – p. 279 – Ogata V
The location of the root locus on the real axis is determined from the open-loop
zero on the negative real axis.
a) If s > -2, then:
(angle condition not satisfied)
b) If s < -2, then:
= 180° (angle condition satisfied)
Thus, the portion of the real axis that lies on the root locus is given by:
𝑆 = −∞, −2
2. Determine the asymptotes of the root loci.
Since there are two open-loop poles and one zero, there is one asymptote, which
coincides with the negative real axis.
54. Example 6–2 – p. 279 – Ogata V
3. Determine the break-in point.
A break-in point exists on the real axis where a pair of root-locus branches
coalesces as K is increased. This is true in this example, because as K increases, the
root loci tend to approach rather than move away from the real axis (which is true
in case of a break-away point).
The break-in point can be found as follows:
which gives
55. Example 6–2 – p. 279 – Ogata V
Notice that point s =–3.7320 is on the root locus. Hence this point is an actual break-
in point.
Also at point s = –3.7320 the corresponding gain value is K = 5.4641.
Since point s = –0.2680 is not on the root locus, it cannot be a break-in point.
4. Determine the points where the root loci cross the imaginary axis.
It can be immediately seen that K = 0 at the complex conjugate poles.
Since both poles lie in the negative half plane, then the root locus cannot cross the
Imaginary axis.
5. Determine the angle of departure from the complex-conjugate open-loop poles.
It is clear that the root locus begins its trip here at the complex-conjugate, where
K = 0.
This requires the determination of the angle of departure from these poles, whose
Knowledge is important.
56. Example 6–2 – p. 279 – Ogata V
Referring to the figure below, we choose a test point and move it in the very vicinity
of the complex open-loop pole at s = –p1 , we find the following:
Angle of departure = θ1.
2tan 1 7.541
902
57. Example 6–2 – p. 279 – Ogata V
Angle condition:
12180211 k
180907.54 1
7.144907.541801
or
3.215180907.541
Which is the same angle.
The value of the gain K at any point on root locus can be found by applying the
magnitude condition or by use of MATLAB.
58. Example 6–2 – p. 279 – Ogata V
Analytic Approach
We shall prove that in this system the root locus in the complex plane is a part of a
circle. Such a circular root locus will not occur in most systems.
Circular root loci may occur in systems that involve two poles and one zero, two
poles and two zeros, or one pole and two zeros.
Even in such systems, whether circular root loci occur depends on the locations of
the poles and zeros involved.
First we need to derive the equation for the root locus.
For the present system, the angle condition is
59. Example 6–2 – p. 279 – Ogata V
which can be written as
or
Taking tangents of both sides of this last equation using the relationship
we obtain
60. Example 6–2 – p. 279 – Ogata V
Thus
which can be simplified to
or
This last equation is equivalent to
Notice that the first equation, ω = 0, is the equation for the real axis. The real axis
from s = –2 to s = –∞ corresponds to a root locus for K ≥ 0.
61. Example 6–2 – p. 279 – Ogata V
The second equation for the root locus is an equation of a circle with a center at
σ = –2, ω = 0 and a radius equal to
That part of the circle to the left of the complex-conjugate poles corresponds to a
root locus for K ≥ 0. The remaining part of the circle corresponds to a root locus when
K is negative.
3
62. Very Important
• Where applicable, the analytic method provides a true
mathematical model for the root loci. MATLAB does not
offer this facility.
• Easily interpretable equations for the root locus can be
derived for simple systems only.
• For complicated systems having many poles and zeros,
any attempt to derive equations for the root loci is
discouraged.
• Such derived equations are very complicated and their
configuration in the complex plane is difficult to
visualize.