Multivariable Feedback Control: Analysis and Design, Second Edition presents a rigorous, yet easily readable, introduction to the analysis and design of robust multivariable control systems. Focusing on practical feedback control and not on system theory in general, this book provides the reader with insights into the opportunities and limitations of feedback control. Taking into account the latest developments in the field, this fully revised and updated second edition: features a new chapter devoted to the use of linear matrix inequalities (LMIs); presents current results on fundamental…mehr
Multivariable Feedback Control: Analysis and Design, Second Edition presents a rigorous, yet easily readable, introduction to the analysis and design of robust multivariable control systems. Focusing on practical feedback control and not on system theory in general, this book provides the reader with insights into the opportunities and limitations of feedback control. Taking into account the latest developments in the field, this fully revised and updated second edition: features a new chapter devoted to the use of linear matrix inequalities (LMIs); presents current results on fundamental performance limitations introduced by RHP poles and RHP zeros; introduces updated material on the selection of controlled variables and self optimizing control; provides simple IMC tuning rules for PID control; covers additional material including unstable plants, the feedback amplifier, the lower gain margin and a clear strategy for incorporating integral action into LQG control; includes numerous worked examples, exercises and case studies, which make frequent use of Matlab and the new Robust Control toolbox. Multivariable Feedback Control: Analysis and Design, Second Edition is an excellent resource for advanced undergraduate and graduate courses studying multivariable control. It is also an invaluable tool for engineers who want to understand multivariable control, its limitations, and how it can be applied in practice. The analysis techniques and the material on control structure design should prove very useful in the new emerging area of systems biology. Reviews of the first edition: "Being rich in insights and practical tips on controller design, the book should also prove to be very beneficial to industrial control engineers, both as a reference book and as an educational tool." Applied Mechanics Reviews "In summary, this book can be strongly recommended not only as a basic text in multivariable control techniques for graduate and undergraduate students, but also as a valuable source of information for control engineers." International Journal of Adaptive Control and Signal ProcessingHinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
Professor Sigurd Skogestad, Norwegian University of Science and Technology (NTNU) Head of the Department of Chemical Engineering. Author of more than 100 journal publications and 150 conference publications. He was awarded "Innstilling to the King" for his Siv.Ing. degree in 1979, a Fullbright fellowship in 1983, received the Ted Peterson Award from AIChE in 1989, the George S. Axelby Outstanding Paper Award from IEEE in 1990, and the O. Hugo Schuck Best Paper Award from the American Automatic Control Council in 1992. Professor Ian Postlethwaite, University of Leicester, UK Head of Engineering Department, Fellow of the Institute of Electrical and Electronics Engineers, Fellow of the Institution of Electrical Engineers, and a Fellow of the Institute of Measurement and Control. In 1991 he received the IEE FC Williams Premium, in 2001 the Sir Harold Hartley Medal of the InstMC and in 2002 the Best Paper Prize for an article published in the IFAC Journal of Control Engineering Practice over the period 1999-2002.
Inhaltsangabe
1 Introduction1 1.1 The process of control system design 1 1.2 The control problem 2 1.3 Transfer functions 3 1.4 Scaling 5 1.5 Deriving linear models 7 1.6 Notation 10 2 Classical Feedback Control 15 2.1 Frequency response 15 2.2 Feedback control 20 2.3 Closed-loop stability 26 2.4 Evaluating closed-loop performance 28 2.5 Controller design 40 2.6 Loop shaping 42 2.7 IMC design procedure and PID control for stable plants 54 2.8 Shaping closed-loop transfer functions 59 2.9 Conclusion 65 3 Introduction to Multivariable Control 67 3.1 Introduction 67 3.2 Transfer functions for MIMO systems 68 3.3 Multivariable frequency response analysis 71 3.4 Relative gain array (RGA) 82 3.5 Control of multivariable plants 91 3.6 Introduction to multivariable RHP-zeros 96 3.7 Introduction to MIMO robustness 98 3.8 General control problem formulation 104 3.9 Additional exercises 115 3.10 Conclusion 117 4 Elements of Linear System Theory 119 4.1 System descriptions 119 4.2 State controllability and state observability 127 4.3 Stability 134 4.4 Poles 135 4.5 Zeros 138 4.6 Some important remarks on poles and zeros 141 4.7 Internal stability of feedback systems 144 4.8 Stabilizing controllers 148 4.9 Stability analysis in the frequency domain 150 4.10 System norms 156 4.11 Conclusion 162 5 Limitations on Performance In Siso Systems 163 5.1 Input-output controllability 163 5.2 Fundamental limitations on sensitivity 167 5.3 Fundamental limitations: bounds on peaks 172 5.4 Perfect control and plant inversion 180 5.5 Ideal ISE optimal control 181 5.6 Limitations imposed by time delays 182 5.7 Limitations imposed by RHP-zeros 183 5.8 Limitations imposed by phase lag 191 5.9 Limitations imposed by unstable (RHP) poles 192 5.10 Performance requirements imposed by disturbances and commands 198 5.11 Limitations imposed by input constraints 199 5.12 Limitations imposed by uncertainty 203 5.13 Summary: controllability analysis with feedback control 206 5.14 Summary: controllability analysis with feedforward control 209 5.15 Applications of controllability analysis 210 5.16 Conclusion 219 6 Limitations on Performance In Mimo Systems 221 6.1 Introduction 221 6.2 Fundamental limitations on sensitivity 222 6.3 Fundamental limitations: bounds on peaks 223 6.4 Functional controllability 232 6.5 Limitations imposed by time delays 233 6.6 Limitations imposed by RHP-zeros 235 6.7 Limitations imposed by unstable (RHP) poles 238 6.8 Performance requirements imposed by disturbance s238 6.9 Limitations imposed by input constraints 240 6.10 Limitations imposed by uncertainty 242 6.11 MIMO input-output controllability 253 6.12 Conclusion 258 7 Uncertainty And Robustness for Siso Systems 259 7.1 Introduction to robustness 259 7.2 Representing uncertainty 260 7.3 Parametric uncertainty 262 7.4 Representing uncertainty in the frequency domain 265 7.5 SISO robust stability 274 7.6 SISO robust performance 281 7.7 Additional exercises 287 7.8 Conclusion 288 8 Robust Stability And Performance Analysis For Mimo Systems 289 8.1 General control configuration with uncertainty 289 8.2 Representing uncertainty 290 8.3 Obtaining P, N and M 298 8.4 Definitions of robust stability and robust performance 299 8.5 Robust stability of the M -structure 301 8.6 Robust stability for complex unstructured uncertainty 302 8.7 Robust stability with structured uncertainty: motivation 305 8.8 The structured singular value 306 8.9 Robust stability with structured uncertainty 313 8.10 Robust performance 316 8.11 Application: robust performance with input uncertainty 320 8.12 -synthesis and DK-iteration 328 8.13 Further remarks on 336 8.14 Conclusion 338 9 Controller Design 341 9.1 Trade-offs in MIMO feedback design 341 9.2 LQG control 344 9.3 H2 and H control 352 9.4 H loop-shaping design 364 9.5 Conclusion 381 10 Control Structure Design 383 10.1 Introduction 383 10.2 Optimal operation and control 385 10.3 Selection of primary controlled outputs 388 10.4 Regulatory control layer 403 10.5 Control configuration elements 420 10.6 Decentralized feedback control 429 10.7 Conclusion 454 11 Model Reduction 455 11.1 Introduction 455 11.2 Truncation and residualization 456 11.3 Balanced realizations 457 11.4 Balanced truncation and balanced residualization 458 11.5 Optimal Hankel norm approximation 459 11.6 Reduction of unstable models 462 11.7 Model reduction using Matlab 462 11.8 Two practical examples 463 11.9 Conclusion 471 12 Linear Matrix Inequalities 473 12.1 Introduction to LMI problems473 12.2 Types of LMI problems 476 12.3 Tricks in LMI problems 479 12.4 Case study: anti-windup compensator synthesis 484 12.5 Conclusion 490 13 Case Studies 491 13.1 Introduction 491 13.2 Helicopter control 492 13.3 Aero-engine control 500 13.4 Distillation process 509 13.5 Conclusion 514 A Matrix Theory And Norms 515 A.1 Basics 515 A.2 Eigenvalues and eigenvectors 518 A.3 Singular value decomposition 520 A.4 Relative gain array 526 A.5 Norms 530 A.6 All-pass factorization of transfer function matrices 541 A.7 Factorization of the sensitivity function 542 A.8 Linear fractional transformations 543 B Project Work And Sample Exam 547 B.1 Project work 547 B.2 Sample exam 548 Bibliography 553 Index 563
1 Introduction1 1.1 The process of control system design 1 1.2 The control problem 2 1.3 Transfer functions 3 1.4 Scaling 5 1.5 Deriving linear models 7 1.6 Notation 10 2 Classical Feedback Control 15 2.1 Frequency response 15 2.2 Feedback control 20 2.3 Closed-loop stability 26 2.4 Evaluating closed-loop performance 28 2.5 Controller design 40 2.6 Loop shaping 42 2.7 IMC design procedure and PID control for stable plants 54 2.8 Shaping closed-loop transfer functions 59 2.9 Conclusion 65 3 Introduction to Multivariable Control 67 3.1 Introduction 67 3.2 Transfer functions for MIMO systems 68 3.3 Multivariable frequency response analysis 71 3.4 Relative gain array (RGA) 82 3.5 Control of multivariable plants 91 3.6 Introduction to multivariable RHP-zeros 96 3.7 Introduction to MIMO robustness 98 3.8 General control problem formulation 104 3.9 Additional exercises 115 3.10 Conclusion 117 4 Elements of Linear System Theory 119 4.1 System descriptions 119 4.2 State controllability and state observability 127 4.3 Stability 134 4.4 Poles 135 4.5 Zeros 138 4.6 Some important remarks on poles and zeros 141 4.7 Internal stability of feedback systems 144 4.8 Stabilizing controllers 148 4.9 Stability analysis in the frequency domain 150 4.10 System norms 156 4.11 Conclusion 162 5 Limitations on Performance In Siso Systems 163 5.1 Input-output controllability 163 5.2 Fundamental limitations on sensitivity 167 5.3 Fundamental limitations: bounds on peaks 172 5.4 Perfect control and plant inversion 180 5.5 Ideal ISE optimal control 181 5.6 Limitations imposed by time delays 182 5.7 Limitations imposed by RHP-zeros 183 5.8 Limitations imposed by phase lag 191 5.9 Limitations imposed by unstable (RHP) poles 192 5.10 Performance requirements imposed by disturbances and commands 198 5.11 Limitations imposed by input constraints 199 5.12 Limitations imposed by uncertainty 203 5.13 Summary: controllability analysis with feedback control 206 5.14 Summary: controllability analysis with feedforward control 209 5.15 Applications of controllability analysis 210 5.16 Conclusion 219 6 Limitations on Performance In Mimo Systems 221 6.1 Introduction 221 6.2 Fundamental limitations on sensitivity 222 6.3 Fundamental limitations: bounds on peaks 223 6.4 Functional controllability 232 6.5 Limitations imposed by time delays 233 6.6 Limitations imposed by RHP-zeros 235 6.7 Limitations imposed by unstable (RHP) poles 238 6.8 Performance requirements imposed by disturbance s238 6.9 Limitations imposed by input constraints 240 6.10 Limitations imposed by uncertainty 242 6.11 MIMO input-output controllability 253 6.12 Conclusion 258 7 Uncertainty And Robustness for Siso Systems 259 7.1 Introduction to robustness 259 7.2 Representing uncertainty 260 7.3 Parametric uncertainty 262 7.4 Representing uncertainty in the frequency domain 265 7.5 SISO robust stability 274 7.6 SISO robust performance 281 7.7 Additional exercises 287 7.8 Conclusion 288 8 Robust Stability And Performance Analysis For Mimo Systems 289 8.1 General control configuration with uncertainty 289 8.2 Representing uncertainty 290 8.3 Obtaining P, N and M 298 8.4 Definitions of robust stability and robust performance 299 8.5 Robust stability of the M -structure 301 8.6 Robust stability for complex unstructured uncertainty 302 8.7 Robust stability with structured uncertainty: motivation 305 8.8 The structured singular value 306 8.9 Robust stability with structured uncertainty 313 8.10 Robust performance 316 8.11 Application: robust performance with input uncertainty 320 8.12 -synthesis and DK-iteration 328 8.13 Further remarks on 336 8.14 Conclusion 338 9 Controller Design 341 9.1 Trade-offs in MIMO feedback design 341 9.2 LQG control 344 9.3 H2 and H control 352 9.4 H loop-shaping design 364 9.5 Conclusion 381 10 Control Structure Design 383 10.1 Introduction 383 10.2 Optimal operation and control 385 10.3 Selection of primary controlled outputs 388 10.4 Regulatory control layer 403 10.5 Control configuration elements 420 10.6 Decentralized feedback control 429 10.7 Conclusion 454 11 Model Reduction 455 11.1 Introduction 455 11.2 Truncation and residualization 456 11.3 Balanced realizations 457 11.4 Balanced truncation and balanced residualization 458 11.5 Optimal Hankel norm approximation 459 11.6 Reduction of unstable models 462 11.7 Model reduction using Matlab 462 11.8 Two practical examples 463 11.9 Conclusion 471 12 Linear Matrix Inequalities 473 12.1 Introduction to LMI problems473 12.2 Types of LMI problems 476 12.3 Tricks in LMI problems 479 12.4 Case study: anti-windup compensator synthesis 484 12.5 Conclusion 490 13 Case Studies 491 13.1 Introduction 491 13.2 Helicopter control 492 13.3 Aero-engine control 500 13.4 Distillation process 509 13.5 Conclusion 514 A Matrix Theory And Norms 515 A.1 Basics 515 A.2 Eigenvalues and eigenvectors 518 A.3 Singular value decomposition 520 A.4 Relative gain array 526 A.5 Norms 530 A.6 All-pass factorization of transfer function matrices 541 A.7 Factorization of the sensitivity function 542 A.8 Linear fractional transformations 543 B Project Work And Sample Exam 547 B.1 Project work 547 B.2 Sample exam 548 Bibliography 553 Index 563
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