Design of Nonlinear Control Systems with the Highest Derivative in Feedback

Size: px
Start display at page:

Download "Design of Nonlinear Control Systems with the Highest Derivative in Feedback"

Transcription

1 SERIES ON STAB1UTY, VIBRATION AND CONTROL OF SYSTEMS SeriesA Volume 16 Founder & Editor: Ardeshir Guran Co-Editors: M. Cloud & W. B. Zimmerman Design of Nonlinear Control Systems with the Highest Derivative in Feedback Valery D. Yurkevich Concoräia University, Canada Y * World Scientific NEWJERSEY LONDON 5INGAP0RE BEIJING SHANGHAI HONG KONG TAIPEI CHENNAi

2 Contents Preface vii 1. Regulär ly and singularly perturbed Systems Regularly perturbed Systems Nonlinear nominal System Linear nominal System Vanishing perturbation Nonvanishing perturbation Singularly perturbed Systems Singular perturbation Two-time-scale motions...; Boundary-layer System Stability analysis Fast and slow-motion Subsystems Degree of time-scale Separation Discrete-time singularly perturbed Systems Fast and slow-motion Subsystems Degree of time-scale Separation Notes Exercises Design goal and reference model Design goal Basic step response parameters Reference model, Notes 30 xiii

3 xiv Design of nordinear control Systems with the highest derivative in feedback 2.5 Exercises 31 Methods of control System design under uncertainty Desired vector field in the state space of plant model Solution of nonlinear inverse dynamics The highest derivative and high gain in feedback loop Differentiating füter and high-gain observer Influence of noise in control system with the highest derivative Desired manifold in the State space of plant model State vector and high gain in feedback loop Control Systems with sliding motions Example Notes Exercises 55 Design of SISO continuous-time control Systems Controller design for plant model of the Ist order Control problem Insensitivity condition Control law with the Ist derivative in feedback loop Closed-loop system properties Controller design for an nth-order plant model Control problem Insensitivity condition Control law with the nth derivative in the feedback loop Fast-motion Subsystem Slow-motion Subsystem Influence of small parameter Geometrie interpretation of control problem Solution Example Notes Exercises 77 Advanced design of SISO continuous-time control Systems Control aecuraey Steady State of fast-motion subsystem Steady State of slow-motion subsystem 80

4 Contents xv Velocity error due to external disturbance Velocity error due to reference input Control law in the form of forward compensator Root placement of FMS characteristic polynomial Degree of time-scale Separation Selection of Controller parameters Root placement based on normalized polynomials Bode amplitude diagram assignment of closed-loop FMS Block diagram of closed-loop System Bode amplitude diagram of closed-loop FMS Desired Bode amplitude diagram of closed-loop FMS Selection of Controller parameters Influence of high-frequency sensor noise Closed-loop System in presence of sensor noise Controller with infinite bandwidth Controller with fmite bandwidth Influence of varying parameters Influence of varying parameters on FMS and SMS Michailov hodograph for FMS Variation of FMS bandwidth Degree of control law differential equation Root placement of FMS characteristic polynomial Bode amplitude diagram assignment of open-loop FMS Relation with PD, PI, and PID Controllers Example Notes Exercises 112 Influence of unmodeled dynamics Pure time delay Plant model with pure time delay in control.. > Closed-loop System with delay in feedback loop Fast motions in presence of delay Stability of FMS with delay Phase margin of FMS with delay Control with compensation of delay Velocity error with respect to external disturbance Example Regulär perturbances 126

5 Design of nonlinear control Systems with the highest derivative in feedback Regularly perturbed plant model Fast motions in presence of regulär perturbances Selection of Controller parameters Control with compensation of regulär perturbances Example Singular perturbances Singularly perturbed plant model Fast motions in presence of singular perturbances Selection of Controller parameters Nonsmooth nonlinearity in control loop System preceded by nonsmooth nonlinearity Describing function analysis of limit cycle in FMS Effect of chattering on control accuracy Example Notes Exercises Realizability of desired output behavior Control problem Statement for MIMO control System MIMO plant model Control problem I Invertibility of dynamical Systems Role of invertibility of dynamical Systems Definition of invertibility of dynamic control System Invertibility condition for nonlinear Systems Insensitivity condition for MIMO control system Desired dynamics equations Insensitivity condition Internal stability Boundedness of jv7.d-control function Concept of internal stability Normal form of the plant model Internal stability of linear Systems Internal stability of nonlinear Systems Degenerated motions and zero-dynamics Example Output regulation of SISO Systems Realizability of desired output behavior Closed-loop System analysis 174

6 Contents Example 7.6 Switching regulator for boost DC-to-DC Converter Boost DC-to-DC Converter circuit model Model with continuous control variable Switching regulator External disturbance attenuation 7.7 Notes 7.8 Exercises Design of MIMO continuous-time control Systems 8.1 MIMO system without internal dynamics MIMO system with identical relative degrees MIMO system with different relative degrees MIMO control system design (identical relative degrees) Lnsensitivity condition Control system with the relative highest derivatives in feedback Fast-motion Subsystem Slow-motion Subsystem Control system design with zero steady-state error Example 8.3 MIMO control system design (different relative degrees) lnsensitivity condition and control law structure Closed-loop system analysis Control accuracy 8.4 MIMO control system in presence of internal dynamics Fast-motion Subsystem Slow-motion Subsystem Example. 8.5 Decentralized Output feedback Controller 8.6 Notes 8.7 Exercises Stabilization of internal dynamics 9.1 Zero placement by redundant control 9.2 Internal dynamics stabilization (particular case) 9.3 Internal dynamics stabilization (generalized case) 9.4 Stabilization of degenerated mode and zero dynamics...

7 Design of nonlinear control Systems with the highest derivative in feedback 9.5 Methods of internal dynamics stabilization Example Notes Exercises 232 Digital Controller design based on pseudo-continuous approach Continuous System preceded by zero-order hold Control problem Pseudo-continuous-time model with pure delay Digital Controller design Insensitivity condition Pseudo-continuous closed-loop System Influence of sampling period Digital realization of continuous Controller Example Digital Controller design with compensation of delay Control law structure Closed-loop System analysis Digital realization of continuous Controller Example Notes Exercises 250 Design of discrete-time control Systems SISO two-time-scale discrete-time control Systems Discrete-time Systems Control problem and insensitivity condition Discrete-time control law Two-time-scale motion analysis Robustness of closed-loop System properties Control accuracy Example SISO discrete-time control Systems with small parameter System with small parameter Two-time-scale motion analysis Interrelationship with fixed point theorem Root placement of FMS characteristic polynomial FMS design based on frequency-domain methods. 274

8 Contents xix 11.3 MIMO two-time-scale discrete-time control Systems MIMO discrete-time Systems Control law Two-time-scale motion analysis Example Notes Exercises Design of sampled-data control Systems SISO sampled-data control Systems Reduced Order pulse transfer function Input-output approximate model of linear system Control law Closed-loop system analysis Selection of Controller parameters Nonlinear sampled-data Systems Example MIMO sampled-data control Systems Control problem MIMO contirmous-time System preceded by ZOH Control law Fast-motion Subsystem Selection of Controller parameters Slow-motion Subsystem Example Notes Exercises Control of distributed parameter Systems One-dimensional heat System with distributed control Heat system with finite-dimensional control Degenerated motions Estimation of modes Notes Exercises 323 Appendix A Proofs 325 A.l Proof of expression (8.29) 325

9 xx Design of nonlinear control Systems with the highest derivative in feedback A.2 Proof of expression (8.42) 325 A.3 Proof of expression (8.65) 32^ A.4 Proof of expression (11.37) 327 A.5 Proof of expressions (11.40)-(11.41) 328 A.6 Proof of expression (11.47) 328 A.7 Proof of expression (11.51) 33 A.8 Proof of expression (12.56) 332 A.9 Proof of expression (12.57) 333 Appendix B Notation system 335 Bibliography Index 349

Contents. PART I METHODS AND CONCEPTS 2. Transfer Function Approach Frequency Domain Representations... 42

Contents. PART I METHODS AND CONCEPTS 2. Transfer Function Approach Frequency Domain Representations... 42 Contents Preface.............................................. xiii 1. Introduction......................................... 1 1.1 Continuous and Discrete Control Systems................. 4 1.2 Open-Loop

More information

1 An Overview and Brief History of Feedback Control 1. 2 Dynamic Models 23. Contents. Preface. xiii

1 An Overview and Brief History of Feedback Control 1. 2 Dynamic Models 23. Contents. Preface. xiii Contents 1 An Overview and Brief History of Feedback Control 1 A Perspective on Feedback Control 1 Chapter Overview 2 1.1 A Simple Feedback System 3 1.2 A First Analysis of Feedback 6 1.3 Feedback System

More information

CONTROL * ~ SYSTEMS ENGINEERING

CONTROL * ~ SYSTEMS ENGINEERING CONTROL * ~ SYSTEMS ENGINEERING H Fourth Edition NormanS. Nise California State Polytechnic University, Pomona JOHN WILEY& SONS, INC. Contents 1. Introduction 1 1.1 Introduction, 2 1.2 A History of Control

More information

CONTROL SYSTEMS ENGINEERING Sixth Edition International Student Version

CONTROL SYSTEMS ENGINEERING Sixth Edition International Student Version CONTROL SYSTEMS ENGINEERING Sixth Edition International Student Version Norman S. Nise California State Polytechnic University, Pomona John Wiley fir Sons, Inc. Contents PREFACE, vii 1. INTRODUCTION, 1

More information

Passivity-based Control of Euler-Lagrange Systems

Passivity-based Control of Euler-Lagrange Systems Romeo Ortega, Antonio Loria, Per Johan Nicklasson and Hebertt Sira-Ramfrez Passivity-based Control of Euler-Lagrange Systems Mechanical, Electrical and Electromechanical Applications Springer Contents

More information

Feedback Control of Dynamic Systems

Feedback Control of Dynamic Systems THIRD EDITION Feedback Control of Dynamic Systems Gene F. Franklin Stanford University J. David Powell Stanford University Abbas Emami-Naeini Integrated Systems, Inc. TT Addison-Wesley Publishing Company

More information

Digital Control Engineering Analysis and Design

Digital Control Engineering Analysis and Design Digital Control Engineering Analysis and Design M. Sami Fadali Antonio Visioli AMSTERDAM BOSTON HEIDELBERG LONDON NEW YORK OXFORD PARIS SAN DIEGO SAN FRANCISCO SINGAPORE SYDNEY TOKYO Academic Press is

More information

Control Design Techniques in Power Electronics Devices

Control Design Techniques in Power Electronics Devices Hebertt Sira-Ramfrez and Ramön Silva-Ortigoza Control Design Techniques in Power Electronics Devices With 202 Figures < } Spri inger g< Contents 1 Introduction 1 Part I Modelling 2 Modelling of DC-to-DC

More information

Introduction to. Process Control. Ahmet Palazoglu. Second Edition. Jose A. Romagnoli. CRC Press. Taylor & Francis Group. Taylor & Francis Group,

Introduction to. Process Control. Ahmet Palazoglu. Second Edition. Jose A. Romagnoli. CRC Press. Taylor & Francis Group. Taylor & Francis Group, Introduction to Process Control Second Edition Jose A. Romagnoli Ahmet Palazoglu CRC Press Taylor & Francis Group Boca Raton London NewYork CRC Press is an imprint of the Taylor & Francis Group, an informa

More information

Mathematical Theory of Control Systems Design

Mathematical Theory of Control Systems Design Mathematical Theory of Control Systems Design by V. N. Afarias'ev, V. B. Kolmanovskii and V. R. Nosov Moscow University of Electronics and Mathematics, Moscow, Russia KLUWER ACADEMIC PUBLISHERS DORDRECHT

More information

Student Solutions Manual for. Design of Nonlinear Control Systems with the Highest Derivative in Feedback

Student Solutions Manual for. Design of Nonlinear Control Systems with the Highest Derivative in Feedback Student Solutions Manual for Design of Nonlinear Control Systems with the Highest Derivative in Feedback World Scientific, 2004 ISBN 981-238-899-0 Valery D. Yurkevich Copyright c 2007 by Valery D. Yurkevich

More information

Chapter 9: Controller design

Chapter 9: Controller design Chapter 9. Controller Design 9.1. Introduction 9.2. Effect of negative feedback on the network transfer functions 9.2.1. Feedback reduces the transfer function from disturbances to the output 9.2.2. Feedback

More information

Outline. Classical Control. Lecture 1

Outline. Classical Control. Lecture 1 Outline Outline Outline 1 Introduction 2 Prerequisites Block diagram for system modeling Modeling Mechanical Electrical Outline Introduction Background Basic Systems Models/Transfers functions 1 Introduction

More information

CDS 101/110a: Lecture 8-1 Frequency Domain Design

CDS 101/110a: Lecture 8-1 Frequency Domain Design CDS 11/11a: Lecture 8-1 Frequency Domain Design Richard M. Murray 17 November 28 Goals: Describe canonical control design problem and standard performance measures Show how to use loop shaping to achieve

More information

FEL3210 Multivariable Feedback Control

FEL3210 Multivariable Feedback Control FEL3210 Multivariable Feedback Control Lecture 5: Uncertainty and Robustness in SISO Systems [Ch.7-(8)] Elling W. Jacobsen, Automatic Control Lab, KTH Lecture 5:Uncertainty and Robustness () FEL3210 MIMO

More information

Feedback Control of Linear SISO systems. Process Dynamics and Control

Feedback Control of Linear SISO systems. Process Dynamics and Control Feedback Control of Linear SISO systems Process Dynamics and Control 1 Open-Loop Process The study of dynamics was limited to open-loop systems Observe process behavior as a result of specific input signals

More information

CDS 101/110a: Lecture 10-1 Robust Performance

CDS 101/110a: Lecture 10-1 Robust Performance CDS 11/11a: Lecture 1-1 Robust Performance Richard M. Murray 1 December 28 Goals: Describe how to represent uncertainty in process dynamics Describe how to analyze a system in the presence of uncertainty

More information

Analysis and Synthesis of Single-Input Single-Output Control Systems

Analysis and Synthesis of Single-Input Single-Output Control Systems Lino Guzzella Analysis and Synthesis of Single-Input Single-Output Control Systems l+kja» \Uja>)W2(ja»\ um Contents 1 Definitions and Problem Formulations 1 1.1 Introduction 1 1.2 Definitions 1 1.2.1 Systems

More information

Robust Control. 2nd class. Spring, 2018 Instructor: Prof. Masayuki Fujita (S5-303B) Tue., 17th April, 2018, 10:45~12:15, S423 Lecture Room

Robust Control. 2nd class. Spring, 2018 Instructor: Prof. Masayuki Fujita (S5-303B) Tue., 17th April, 2018, 10:45~12:15, S423 Lecture Room Robust Control Spring, 2018 Instructor: Prof. Masayuki Fujita (S5-303B) 2nd class Tue., 17th April, 2018, 10:45~12:15, S423 Lecture Room 2. Nominal Performance 2.1 Weighted Sensitivity [SP05, Sec. 2.8,

More information

Today (10/23/01) Today. Reading Assignment: 6.3. Gain/phase margin lead/lag compensator Ref. 6.4, 6.7, 6.10

Today (10/23/01) Today. Reading Assignment: 6.3. Gain/phase margin lead/lag compensator Ref. 6.4, 6.7, 6.10 Today Today (10/23/01) Gain/phase margin lead/lag compensator Ref. 6.4, 6.7, 6.10 Reading Assignment: 6.3 Last Time In the last lecture, we discussed control design through shaping of the loop gain GK:

More information

Control Systems II. ETH, MAVT, IDSC, Lecture 4 17/03/2017. G. Ducard

Control Systems II. ETH, MAVT, IDSC, Lecture 4 17/03/2017. G. Ducard Control Systems II ETH, MAVT, IDSC, Lecture 4 17/03/2017 Lecture plan: Control Systems II, IDSC, 2017 SISO Control Design 24.02 Lecture 1 Recalls, Introductory case study 03.03 Lecture 2 Cascaded Control

More information

Automatic Control 2. Loop shaping. Prof. Alberto Bemporad. University of Trento. Academic year

Automatic Control 2. Loop shaping. Prof. Alberto Bemporad. University of Trento. Academic year Automatic Control 2 Loop shaping Prof. Alberto Bemporad University of Trento Academic year 21-211 Prof. Alberto Bemporad (University of Trento) Automatic Control 2 Academic year 21-211 1 / 39 Feedback

More information

YTÜ Mechanical Engineering Department

YTÜ Mechanical Engineering Department YTÜ Mechanical Engineering Department Lecture of Special Laboratory of Machine Theory, System Dynamics and Control Division Coupled Tank 1 Level Control with using Feedforward PI Controller Lab Report

More information

Dr Ian R. Manchester Dr Ian R. Manchester AMME 3500 : Review

Dr Ian R. Manchester Dr Ian R. Manchester AMME 3500 : Review Week Date Content Notes 1 6 Mar Introduction 2 13 Mar Frequency Domain Modelling 3 20 Mar Transient Performance and the s-plane 4 27 Mar Block Diagrams Assign 1 Due 5 3 Apr Feedback System Characteristics

More information

Lecture 2. Introduction to Systems (Lathi )

Lecture 2. Introduction to Systems (Lathi ) Lecture 2 Introduction to Systems (Lathi 1.6-1.8) Pier Luigi Dragotti Department of Electrical & Electronic Engineering Imperial College London URL: www.commsp.ee.ic.ac.uk/~pld/teaching/ E-mail: p.dragotti@imperial.ac.uk

More information

Process Modelling, Identification, and Control

Process Modelling, Identification, and Control Jan Mikles Miroslav Fikar 2008 AGI-Information Management Consultants May be used for personal purporses only or by libraries associated to dandelon.com network. Process Modelling, Identification, and

More information

DURING the last two decades since the publication of the

DURING the last two decades since the publication of the 328 IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY, VOL 7, NO 3, MAY 1999 A Control Engineer s Guide to Sliding Mode Control K David Young, Senior Member, IEEE, Vadim I Utkin, Senior Member, IEEE, and

More information

CHAPTER 5 ROBUSTNESS ANALYSIS OF THE CONTROLLER

CHAPTER 5 ROBUSTNESS ANALYSIS OF THE CONTROLLER 114 CHAPTER 5 ROBUSTNESS ANALYSIS OF THE CONTROLLER 5.1 INTRODUCTION Robust control is a branch of control theory that explicitly deals with uncertainty in its approach to controller design. It also refers

More information

The output voltage is given by,

The output voltage is given by, 71 The output voltage is given by, = (3.1) The inductor and capacitor values of the Boost converter are derived by having the same assumption as that of the Buck converter. Now the critical value of the

More information

Chapter 9 Robust Stability in SISO Systems 9. Introduction There are many reasons to use feedback control. As we have seen earlier, with the help of a

Chapter 9 Robust Stability in SISO Systems 9. Introduction There are many reasons to use feedback control. As we have seen earlier, with the help of a Lectures on Dynamic Systems and Control Mohammed Dahleh Munther A. Dahleh George Verghese Department of Electrical Engineering and Computer Science Massachuasetts Institute of Technology c Chapter 9 Robust

More information

ECSE 4962 Control Systems Design. A Brief Tutorial on Control Design

ECSE 4962 Control Systems Design. A Brief Tutorial on Control Design ECSE 4962 Control Systems Design A Brief Tutorial on Control Design Instructor: Professor John T. Wen TA: Ben Potsaid http://www.cat.rpi.edu/~wen/ecse4962s04/ Don t Wait Until The Last Minute! You got

More information

RELAY CONTROL WITH PARALLEL COMPENSATOR FOR NONMINIMUM PHASE PLANTS. Ryszard Gessing

RELAY CONTROL WITH PARALLEL COMPENSATOR FOR NONMINIMUM PHASE PLANTS. Ryszard Gessing RELAY CONTROL WITH PARALLEL COMPENSATOR FOR NONMINIMUM PHASE PLANTS Ryszard Gessing Politechnika Śl aska Instytut Automatyki, ul. Akademicka 16, 44-101 Gliwice, Poland, fax: +4832 372127, email: gessing@ia.gliwice.edu.pl

More information

The loop shaping paradigm. Lecture 7. Loop analysis of feedback systems (2) Essential specifications (2)

The loop shaping paradigm. Lecture 7. Loop analysis of feedback systems (2) Essential specifications (2) Lecture 7. Loop analysis of feedback systems (2). Loop shaping 2. Performance limitations The loop shaping paradigm. Estimate performance and robustness of the feedback system from the loop transfer L(jω)

More information

Sliding Modes in Control and Optimization

Sliding Modes in Control and Optimization Vadim I. Utkin Sliding Modes in Control and Optimization With 24 Figures Springer-Verlag Berlin Heidelberg New York London Paris Tokyo Hong Kong Barcelona Budapest Contents Parti. Mathematical Tools 1

More information

Index. Index. More information. in this web service Cambridge University Press

Index. Index. More information.  in this web service Cambridge University Press A-type elements, 4 7, 18, 31, 168, 198, 202, 219, 220, 222, 225 A-type variables. See Across variable ac current, 172, 251 ac induction motor, 251 Acceleration rotational, 30 translational, 16 Accumulator,

More information

Where rank (B) =m and (A, B) is a controllable pair and the switching function is represented as

Where rank (B) =m and (A, B) is a controllable pair and the switching function is represented as Rev. éc. Ing. Univ. Zulia. Vol. 39, Nº 8, 1-6, 16 doi:1.1311/1.39.8.3 Optimal Sliding Surface Design for a MIMO Distillation System Senthil Kumar B 1 *, K.Suresh Manic 1 Research Scholar, Faculty of Electrical

More information

SECTION 4: STEADY STATE ERROR

SECTION 4: STEADY STATE ERROR SECTION 4: STEADY STATE ERROR MAE 4421 Control of Aerospace & Mechanical Systems 2 Introduction Steady State Error Introduction 3 Consider a simple unity feedback system The error is the difference between

More information

(Continued on next page)

(Continued on next page) (Continued on next page) 18.2 Roots of Stability Nyquist Criterion 87 e(s) 1 S(s) = =, r(s) 1 + P (s)c(s) where P (s) represents the plant transfer function, and C(s) the compensator. The closedloop characteristic

More information

Design Methods for Control Systems

Design Methods for Control Systems Design Methods for Control Systems Maarten Steinbuch TU/e Gjerrit Meinsma UT Dutch Institute of Systems and Control Winter term 2002-2003 Schedule November 25 MSt December 2 MSt Homework # 1 December 9

More information

Process Modelling, Identification, and Control

Process Modelling, Identification, and Control Jan Mikles Miroslav Fikar Process Modelling, Identification, and Control With 187 Figures and 13 Tables 4u Springer Contents 1 Introduction 1 1.1 Topics in Process Control 1 1.2 An Example of Process Control

More information

Electronic Throttle Valve Control Design Based on Sliding Mode Perturbation Estimator

Electronic Throttle Valve Control Design Based on Sliding Mode Perturbation Estimator on Sliding Mode Perturbation Estimator Asst. Prof. Dr. Shibly Ahmed Al-Samarraie, Lect. Yasir Khudhair Al-Nadawi, Mustafa Hussein Mishary, Muntadher Mohammed Salih Control & Systems Engineering Department,

More information

Control Systems. LMIs in. Guang-Ren Duan. Analysis, Design and Applications. Hai-Hua Yu. CRC Press. Taylor & Francis Croup

Control Systems. LMIs in. Guang-Ren Duan. Analysis, Design and Applications. Hai-Hua Yu. CRC Press. Taylor & Francis Croup LMIs in Control Systems Analysis, Design and Applications Guang-Ren Duan Hai-Hua Yu CRC Press Taylor & Francis Croup Boca Raton London New York CRC Press is an imprint of the Taylor & Francis Croup, an

More information

Table of Laplacetransform

Table of Laplacetransform Appendix Table of Laplacetransform pairs 1(t) f(s) oct), unit impulse at t = 0 a, a constant or step of magnitude a at t = 0 a s t, a ramp function e- at, an exponential function s + a sin wt, a sine fun

More information

CBE507 LECTURE III Controller Design Using State-space Methods. Professor Dae Ryook Yang

CBE507 LECTURE III Controller Design Using State-space Methods. Professor Dae Ryook Yang CBE507 LECTURE III Controller Design Using State-space Methods Professor Dae Ryook Yang Fall 2013 Dept. of Chemical and Biological Engineering Korea University Korea University III -1 Overview States What

More information

A brief introduction to robust H control

A brief introduction to robust H control A brief introduction to robust H control Jean-Marc Biannic System Control and Flight Dynamics Department ONERA, Toulouse. http://www.onera.fr/staff/jean-marc-biannic/ http://jm.biannic.free.fr/ European

More information

YTÜ Mechanical Engineering Department

YTÜ Mechanical Engineering Department YTÜ Mechanical Engineering Department Lecture of Special Laboratory of Machine Theory, System Dynamics and Control Division Coupled Tank 1 Level Control with using Feedforward PI Controller Lab Date: Lab

More information

CONTROL OF DIGITAL SYSTEMS

CONTROL OF DIGITAL SYSTEMS AUTOMATIC CONTROL AND SYSTEM THEORY CONTROL OF DIGITAL SYSTEMS Gianluca Palli Dipartimento di Ingegneria dell Energia Elettrica e dell Informazione (DEI) Università di Bologna Email: gianluca.palli@unibo.it

More information

FREQUENCY-RESPONSE DESIGN

FREQUENCY-RESPONSE DESIGN ECE45/55: Feedback Control Systems. 9 FREQUENCY-RESPONSE DESIGN 9.: PD and lead compensation networks The frequency-response methods we have seen so far largely tell us about stability and stability margins

More information

Feedback design for the Buck Converter

Feedback design for the Buck Converter Feedback design for the Buck Converter Portland State University Department of Electrical and Computer Engineering Portland, Oregon, USA December 30, 2009 Abstract In this paper we explore two compensation

More information

Loop-Shaping Controller Design from Input-Output Data

Loop-Shaping Controller Design from Input-Output Data Loop-Shaping Controller Design from Input-Output Data Kostas Tsakalis, Sachi Dash, ASU Honeywell HTC Control-Oriented ID: Uncertainty description compatible with the controller design method. (Loop-Shaping

More information

Chapter Stability Robustness Introduction Last chapter showed how the Nyquist stability criterion provides conditions for the stability robustness of

Chapter Stability Robustness Introduction Last chapter showed how the Nyquist stability criterion provides conditions for the stability robustness of Lectures on Dynamic Systems and Control Mohammed Dahleh Munther A Dahleh George Verghese Department of Electrical Engineering and Computer Science Massachuasetts Institute of Technology c Chapter Stability

More information

CYBER EXPLORATION LABORATORY EXPERIMENTS

CYBER EXPLORATION LABORATORY EXPERIMENTS CYBER EXPLORATION LABORATORY EXPERIMENTS 1 2 Cyber Exploration oratory Experiments Chapter 2 Experiment 1 Objectives To learn to use MATLAB to: (1) generate polynomial, (2) manipulate polynomials, (3)

More information

Stability of CL System

Stability of CL System Stability of CL System Consider an open loop stable system that becomes unstable with large gain: At the point of instability, K( j) G( j) = 1 0dB K( j) G( j) K( j) G( j) K( j) G( j) =± 180 o 180 o Closed

More information

Geometric Control Theory

Geometric Control Theory 1 Geometric Control Theory Lecture notes by Xiaoming Hu and Anders Lindquist in collaboration with Jorge Mari and Janne Sand 2012 Optimization and Systems Theory Royal institute of technology SE-100 44

More information

Chapter 2. Classical Control System Design. Dutch Institute of Systems and Control

Chapter 2. Classical Control System Design. Dutch Institute of Systems and Control Chapter 2 Classical Control System Design Overview Ch. 2. 2. Classical control system design Introduction Introduction Steady-state Steady-state errors errors Type Type k k systems systems Integral Integral

More information

Unit 8: Part 2: PD, PID, and Feedback Compensation

Unit 8: Part 2: PD, PID, and Feedback Compensation Ideal Derivative Compensation (PD) Lead Compensation PID Controller Design Feedback Compensation Physical Realization of Compensation Unit 8: Part 2: PD, PID, and Feedback Compensation Engineering 5821:

More information

6.302 Feedback Systems Recitation 16: Compensation Prof. Joel L. Dawson

6.302 Feedback Systems Recitation 16: Compensation Prof. Joel L. Dawson Bode Obstacle Course is one technique for doing compensation, or designing a feedback system to make the closed-loop behavior what we want it to be. To review: - G c (s) G(s) H(s) you are here! plant For

More information

Closed-loop system 2/1/2016. Generally MIMO case. Two-degrees-of-freedom (2 DOF) control structure. (2 DOF structure) The closed loop equations become

Closed-loop system 2/1/2016. Generally MIMO case. Two-degrees-of-freedom (2 DOF) control structure. (2 DOF structure) The closed loop equations become Closed-loop system enerally MIMO case Two-degrees-of-freedom (2 DOF) control structure (2 DOF structure) 2 The closed loop equations become solving for z gives where is the closed loop transfer function

More information

Control System Design

Control System Design ELEC ENG 4CL4: Control System Design Notes for Lecture #11 Wednesday, January 28, 2004 Dr. Ian C. Bruce Room: CRL-229 Phone ext.: 26984 Email: ibruce@mail.ece.mcmaster.ca Relative Stability: Stability

More information

Feedback Linearization based Arc Length Control for Gas Metal Arc Welding

Feedback Linearization based Arc Length Control for Gas Metal Arc Welding 5 American Control Conference June 8-, 5. Portland, OR, USA FrA5.6 Feedback Linearization based Arc Length Control for Gas Metal Arc Welding Jesper S. Thomsen Abstract In this paper a feedback linearization

More information

KINGS COLLEGE OF ENGINEERING DEPARTMENT OF ELECTRONICS AND COMMUNICATION ENGINEERING

KINGS COLLEGE OF ENGINEERING DEPARTMENT OF ELECTRONICS AND COMMUNICATION ENGINEERING KINGS COLLEGE OF ENGINEERING DEPARTMENT OF ELECTRONICS AND COMMUNICATION ENGINEERING QUESTION BANK SUB.NAME : CONTROL SYSTEMS BRANCH : ECE YEAR : II SEMESTER: IV 1. What is control system? 2. Define open

More information

Index Accumulation, 53 Accuracy: numerical integration, sensor, 383, Adaptive tuning: expert system, 528 gain scheduling, 518, 529, 709,

Index Accumulation, 53 Accuracy: numerical integration, sensor, 383, Adaptive tuning: expert system, 528 gain scheduling, 518, 529, 709, Accumulation, 53 Accuracy: numerical integration, 83-84 sensor, 383, 772-773 Adaptive tuning: expert system, 528 gain scheduling, 518, 529, 709, 715 input conversion, 519 reasons for, 512-517 relay auto-tuning,

More information

Department of Electronics and Instrumentation Engineering M. E- CONTROL AND INSTRUMENTATION ENGINEERING CL7101 CONTROL SYSTEM DESIGN Unit I- BASICS AND ROOT-LOCUS DESIGN PART-A (2 marks) 1. What are the

More information

GAIN SCHEDULING CONTROL WITH MULTI-LOOP PID FOR 2- DOF ARM ROBOT TRAJECTORY CONTROL

GAIN SCHEDULING CONTROL WITH MULTI-LOOP PID FOR 2- DOF ARM ROBOT TRAJECTORY CONTROL GAIN SCHEDULING CONTROL WITH MULTI-LOOP PID FOR 2- DOF ARM ROBOT TRAJECTORY CONTROL 1 KHALED M. HELAL, 2 MOSTAFA R.A. ATIA, 3 MOHAMED I. ABU EL-SEBAH 1, 2 Mechanical Engineering Department ARAB ACADEMY

More information

CHAPTER 4 STATE FEEDBACK AND OUTPUT FEEDBACK CONTROLLERS

CHAPTER 4 STATE FEEDBACK AND OUTPUT FEEDBACK CONTROLLERS 54 CHAPTER 4 STATE FEEDBACK AND OUTPUT FEEDBACK CONTROLLERS 4.1 INTRODUCTION In control theory, a controller is a device which monitors and affects the operational conditions of a given dynamic system.

More information

Boundary. DIFFERENTIAL EQUATIONS with Fourier Series and. Value Problems APPLIED PARTIAL. Fifth Edition. Richard Haberman PEARSON

Boundary. DIFFERENTIAL EQUATIONS with Fourier Series and. Value Problems APPLIED PARTIAL. Fifth Edition. Richard Haberman PEARSON APPLIED PARTIAL DIFFERENTIAL EQUATIONS with Fourier Series and Boundary Value Problems Fifth Edition Richard Haberman Southern Methodist University PEARSON Boston Columbus Indianapolis New York San Francisco

More information

Dynamics and control of mechanical systems

Dynamics and control of mechanical systems Dynamics and control of mechanical systems Date Day 1 (03/05) - 05/05 Day 2 (07/05) Day 3 (09/05) Day 4 (11/05) Day 5 (14/05) Day 6 (16/05) Content Review of the basics of mechanics. Kinematics of rigid

More information

Control Systems Design

Control Systems Design ELEC4410 Control Systems Design Lecture 3, Part 2: Introduction to Affine Parametrisation School of Electrical Engineering and Computer Science Lecture 3, Part 2: Affine Parametrisation p. 1/29 Outline

More information

Control Systems. State Estimation.

Control Systems. State Estimation. State Estimation chibum@seoultech.ac.kr Outline Dominant pole design Symmetric root locus State estimation We are able to place the CLPs arbitrarily by feeding back all the states: u = Kx. But these may

More information

Chapter 3. State Feedback - Pole Placement. Motivation

Chapter 3. State Feedback - Pole Placement. Motivation Chapter 3 State Feedback - Pole Placement Motivation Whereas classical control theory is based on output feedback, this course mainly deals with control system design by state feedback. This model-based

More information

State Regulator. Advanced Control. design of controllers using pole placement and LQ design rules

State Regulator. Advanced Control. design of controllers using pole placement and LQ design rules Advanced Control State Regulator Scope design of controllers using pole placement and LQ design rules Keywords pole placement, optimal control, LQ regulator, weighting matrixes Prerequisites Contact state

More information

AS A POPULAR approach for compensating external

AS A POPULAR approach for compensating external IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY, VOL. 16, NO. 1, JANUARY 2008 137 A Novel Robust Nonlinear Motion Controller With Disturbance Observer Zi-Jiang Yang, Hiroshi Tsubakihara, Shunshoku Kanae,

More information

1 Loop Control. 1.1 Open-loop. ISS0065 Control Instrumentation

1 Loop Control. 1.1 Open-loop. ISS0065 Control Instrumentation Lecture 4 ISS0065 Control Instrumentation 1 Loop Control System has a continuous signal (analog) basic notions: open-loop control, close-loop control. 1.1 Open-loop Open-loop / avatud süsteem / открытая

More information

ANALYSIS AND SYNTHESIS OF DISTURBANCE OBSERVER AS AN ADD-ON ROBUST CONTROLLER

ANALYSIS AND SYNTHESIS OF DISTURBANCE OBSERVER AS AN ADD-ON ROBUST CONTROLLER ANALYSIS AND SYNTHESIS OF DISTURBANCE OBSERVER AS AN ADD-ON ROBUST CONTROLLER Hyungbo Shim (School of Electrical Engineering, Seoul National University, Korea) in collaboration with Juhoon Back, Nam Hoon

More information

3.1 Overview 3.2 Process and control-loop interactions

3.1 Overview 3.2 Process and control-loop interactions 3. Multivariable 3.1 Overview 3.2 and control-loop interactions 3.2.1 Interaction analysis 3.2.2 Closed-loop stability 3.3 Decoupling control 3.3.1 Basic design principle 3.3.2 Complete decoupling 3.3.3

More information

Singular Value Decomposition Analysis

Singular Value Decomposition Analysis Singular Value Decomposition Analysis Singular Value Decomposition Analysis Introduction Introduce a linear algebra tool: singular values of a matrix Motivation Why do we need singular values in MIMO control

More information

H -Optimal Control and Related Minimax Design Problems

H -Optimal Control and Related Minimax Design Problems Tamer Başar Pierre Bernhard H -Optimal Control and Related Minimax Design Problems A Dynamic Game Approach Second Edition 1995 Birkhäuser Boston Basel Berlin Contents Preface v 1 A General Introduction

More information

1 Chapter 9: Design via Root Locus

1 Chapter 9: Design via Root Locus 1 Figure 9.1 a. Sample root locus, showing possible design point via gain adjustment (A) and desired design point that cannot be met via simple gain adjustment (B); b. responses from poles at A and B 2

More information

SAMPLE SOLUTION TO EXAM in MAS501 Control Systems 2 Autumn 2015

SAMPLE SOLUTION TO EXAM in MAS501 Control Systems 2 Autumn 2015 FACULTY OF ENGINEERING AND SCIENCE SAMPLE SOLUTION TO EXAM in MAS501 Control Systems 2 Autumn 2015 Lecturer: Michael Ruderman Problem 1: Frequency-domain analysis and control design (15 pt) Given is a

More information

PERIODIC signals are commonly experienced in industrial

PERIODIC signals are commonly experienced in industrial IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY, VOL. 15, NO. 2, MARCH 2007 369 Repetitive Learning Control of Nonlinear Continuous-Time Systems Using Quasi-Sliding Mode Xiao-Dong Li, Tommy W. S. Chow,

More information

Control System Design

Control System Design ELEC ENG 4CL4: Control System Design Notes for Lecture #14 Wednesday, February 5, 2003 Dr. Ian C. Bruce Room: CRL-229 Phone ext.: 26984 Email: ibruce@mail.ece.mcmaster.ca Chapter 7 Synthesis of SISO Controllers

More information

MIMO analysis: loop-at-a-time

MIMO analysis: loop-at-a-time MIMO robustness MIMO analysis: loop-at-a-time y 1 y 2 P (s) + + K 2 (s) r 1 r 2 K 1 (s) Plant: P (s) = 1 s 2 + α 2 s α 2 α(s + 1) α(s + 1) s α 2. (take α = 10 in the following numerical analysis) Controller:

More information

Simple Learning Control Made Practical by Zero-Phase Filtering: Applications to Robotics

Simple Learning Control Made Practical by Zero-Phase Filtering: Applications to Robotics IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS I: FUNDAMENTAL THEORY AND APPLICATIONS, VOL 49, NO 6, JUNE 2002 753 Simple Learning Control Made Practical by Zero-Phase Filtering: Applications to Robotics Haluk

More information

Stochastic Models, Estimation and Control Peter S. Maybeck Volumes 1, 2 & 3 Tables of Contents

Stochastic Models, Estimation and Control Peter S. Maybeck Volumes 1, 2 & 3 Tables of Contents Navtech Part #s Volume 1 #1277 Volume 2 #1278 Volume 3 #1279 3 Volume Set #1280 Stochastic Models, Estimation and Control Peter S. Maybeck Volumes 1, 2 & 3 Tables of Contents Volume 1 Preface Contents

More information

Repetitive control : Power Electronics. Applications

Repetitive control : Power Electronics. Applications Repetitive control : Power Electronics Applications Ramon Costa Castelló Advanced Control of Energy Systems (ACES) Instituto de Organización y Control (IOC) Universitat Politècnica de Catalunya (UPC) Barcelona,

More information

Goodwin, Graebe, Salgado, Prentice Hall Chapter 11. Chapter 11. Dealing with Constraints

Goodwin, Graebe, Salgado, Prentice Hall Chapter 11. Chapter 11. Dealing with Constraints Chapter 11 Dealing with Constraints Topics to be covered An ubiquitous problem in control is that all real actuators have limited authority. This implies that they are constrained in amplitude and/or rate

More information

CBE495 LECTURE IV MODEL PREDICTIVE CONTROL

CBE495 LECTURE IV MODEL PREDICTIVE CONTROL What is Model Predictive Control (MPC)? CBE495 LECTURE IV MODEL PREDICTIVE CONTROL Professor Dae Ryook Yang Fall 2013 Dept. of Chemical and Biological Engineering Korea University * Some parts are from

More information

Lecture 12. Upcoming labs: Final Exam on 12/21/2015 (Monday)10:30-12:30

Lecture 12. Upcoming labs: Final Exam on 12/21/2015 (Monday)10:30-12:30 289 Upcoming labs: Lecture 12 Lab 20: Internal model control (finish up) Lab 22: Force or Torque control experiments [Integrative] (2-3 sessions) Final Exam on 12/21/2015 (Monday)10:30-12:30 Today: Recap

More information

Alexander Scheinker Miroslav Krstić. Model-Free Stabilization by Extremum Seeking

Alexander Scheinker Miroslav Krstić. Model-Free Stabilization by Extremum Seeking Alexander Scheinker Miroslav Krstić Model-Free Stabilization by Extremum Seeking 123 Preface Originating in 1922, in its 95-year history, extremum seeking has served as a tool for model-free real-time

More information

EQUATION LANGEVIN. Physics, Chemistry and Electrical Engineering. World Scientific. With Applications to Stochastic Problems in. William T.

EQUATION LANGEVIN. Physics, Chemistry and Electrical Engineering. World Scientific. With Applications to Stochastic Problems in. William T. SHANGHAI HONG WorlrfScientific Series krtonttimfjorary Chemical Physics-Vol. 27 THE LANGEVIN EQUATION With Applications to Stochastic Problems in Physics, Chemistry and Electrical Engineering Third Edition

More information

Topic # Feedback Control Systems

Topic # Feedback Control Systems Topic #19 16.31 Feedback Control Systems Stengel Chapter 6 Question: how well do the large gain and phase margins discussed for LQR map over to DOFB using LQR and LQE (called LQG)? Fall 2010 16.30/31 19

More information

EECE 460 : Control System Design

EECE 460 : Control System Design EECE 460 : Control System Design SISO Pole Placement Guy A. Dumont UBC EECE January 2011 Guy A. Dumont (UBC EECE) EECE 460: Pole Placement January 2011 1 / 29 Contents 1 Preview 2 Polynomial Pole Placement

More information

FEEDBACK CONTROL SYSTEMS

FEEDBACK CONTROL SYSTEMS FEEDBAC CONTROL SYSTEMS. Control System Design. Open and Closed-Loop Control Systems 3. Why Closed-Loop Control? 4. Case Study --- Speed Control of a DC Motor 5. Steady-State Errors in Unity Feedback Control

More information

EE 422G - Signals and Systems Laboratory

EE 422G - Signals and Systems Laboratory EE 4G - Signals and Systems Laboratory Lab 9 PID Control Kevin D. Donohue Department of Electrical and Computer Engineering University of Kentucky Lexington, KY 40506 April, 04 Objectives: Identify the

More information

Design and Tuning of Fractional-order PID Controllers for Time-delayed Processes

Design and Tuning of Fractional-order PID Controllers for Time-delayed Processes Design and Tuning of Fractional-order PID Controllers for Time-delayed Processes Emmanuel Edet Technology and Innovation Centre University of Strathclyde 99 George Street Glasgow, United Kingdom emmanuel.edet@strath.ac.uk

More information

Quantum Mechanics: Foundations and Applications

Quantum Mechanics: Foundations and Applications Arno Böhm Quantum Mechanics: Foundations and Applications Third Edition, Revised and Enlarged Prepared with Mark Loewe With 96 Illustrations Springer-Verlag New York Berlin Heidelberg London Paris Tokyo

More information

Applied Nonlinear Control

Applied Nonlinear Control Applied Nonlinear Control JEAN-JACQUES E. SLOTINE Massachusetts Institute of Technology WEIPING LI Massachusetts Institute of Technology Pearson Education Prentice Hall International Inc. Upper Saddle

More information

Interferometric. Gravitational Wav. Detectors. \p World Scientific. Fundamentals of. Peter R. Sawlson. Syracuse University, USA.

Interferometric. Gravitational Wav. Detectors. \p World Scientific. Fundamentals of. Peter R. Sawlson. Syracuse University, USA. SINGAPORE HONGKONG Fundamentals of Interferometric Gravitational Wav Detectors Second Edition Peter R. Sawlson Martin A. Pomerantz '37 Professor of Physics Syracuse University, USA \p World Scientific

More information

Introduction to Aircraft Flight. Mechanics

Introduction to Aircraft Flight. Mechanics Introduction to Aircraft Flight. Mechanics i Performance, Static Stability, Dynamic Stability, Classical Feedback Control, and State-Space Foundations Second Edition Thomas R. Yechout with contributions

More information

Optimal Control and Viscosity Solutions of Hamilton-Jacobi-Bellman Equations

Optimal Control and Viscosity Solutions of Hamilton-Jacobi-Bellman Equations Martino Bardi Italo Capuzzo-Dolcetta Optimal Control and Viscosity Solutions of Hamilton-Jacobi-Bellman Equations Birkhauser Boston Basel Berlin Contents Preface Basic notations xi xv Chapter I. Outline

More information