Cover image for Control system design
Title:
Control system design
Publication Information:
Upper Saddle River, N.J. : Prentice Hall, 2001
ISBN:
9780139586538
General Note:
Accompanies text with the call no. : (TS213 G72 2001)

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Summary

Summary

For both undergraduate and graduate courses in Control System Design.

Using a "how to do it" approach with a strong emphasis on real-world design, this text provides comprehensive, single-source coverage of the full spectrum of control system design. Each of the text's 8 parts covers an area in control--ranging from signals and systems (Bode Diagrams, Root Locus, etc.), to SISO control (including PID and Fundamental Design Trade-Offs) and MIMO systems (including Constraints, MPC, Decoupling, etc.).


Author Notes

GRAHAM GOODWIN has over 30 years of experience in the area of control engineering covering research, education and industry. He is the author of seven books, 500 papers and holds four patents. He was the foundation Chairman of a spin-off company and is currently Directory of a special research center dedicated to systems and control research.

STEFAN GRAEBE 's career spans both academic and industrial positions. He was previously research coordinator in the Centre for Industrial Control Science at the University of Newcastle. He is currently head of the Department of Optimization and Automation for the Schwechat refinery of OMV Austria.

MARIO SALGADO received a Maters degree in Control from Imperial College and a Ph.D. from the University of Newcastle. He is currently an academic in the Department of Electronics at the Universidad Tecnica Frederico Santa Maria, Valparaìso Chile. His interests include signal processing and control systems design.


Excerpts

Excerpts

PREFACE Introduction to Control Engineering Control Engineering plays a fundamental role in modern technological systems. The benefits of improved control in industry can be immense. They include improved product quality, reduced energy consumption, minimization of waste material, increased safety levels, and reduction of pollution. A difficulty with the subject, however, is that some of the more advanced aspects depend on a sophisticated mathematical background. Arguably, mathematical systems theory is one of the most significant achievements of twentieth-century science, but its practical impact is only as important as the benefits it can bring. Thus, we include in this book a strong emphasis on design, ultimately striking a balance between theory and practice. It was the authors' involvement in several industrial control-system design projects that provided part of the motivation to write this book. In a typical industrial problem, we found ourselves investigating fluid and thermal dynamics, experiencing the detrimental effects of nonconstant PLC scan rates, dealing with system integration and network communication protocols, building trust with plant operators, and investigating safe bumpless transfer schemes for testing tentative control designs on potentially dangerous plants. In short, we experienced the day-to-day excitement, frustration, set-backs, and progress in getting advanced control to contribute to a commercial company's bottom line. This is not an easy task. Success in this type of venture typically depends on the application of a wide range of multidisciplinary skills; however, it is rewarding and exciting work for those who do it. One of the main aims of this book is to share this excitement with our readers. We hope to contribute to the development of skills and attitudes within readers and students that will better equip them to face the challenges of real-world design problems. The book is thus intended to contribute to the ongoing reform of the Control Engineering curriculum. This topic continues to receive considerable international attention as educators strive to convey the excitement and importance of control engineering. Indeed, entire issues of the IEEE Control Systems Magazine have been devoted to this theme. Reforming the curriculum will not, however, be done by books alone. It will be done by people: students, teachers, researchers, practitioners, publication and grant reviewers, and by market pressures. Moreover, for these efforts to be efficient and sustainable, the control engineering community will need to communicate their experiences via a host of new books, laboratories, simulations, and web-based resources. Thus, there will be a need for several different and complementary approaches. In this context, the authors believe that this book will have been successful if it contributes, in some way, to the revitalization of interest by students in the exciting discipline of control engineering. We stress that this is not a how-to book. On the contrary, we provide a comprehensive, yet condensed, presentation of rigorous control engineering. We employ, and thus require, mathematics as a means to model the process, analyze its properties under feedback, synthesize a controller with particular properties, and arrive at a design addressing the inherent trade-offs and constraints applicable to the problem. In particular, we believe that success in control projects depends on two key ingredients: (i) having a comprehensive understanding of the process itself, gained by studying the relevant physics, chemistry, and so on; and (ii) by having mastery of the fundamental concepts of signals, systems, and feedback. The first ingredient typically occupies more than fifty per cent of the effort. It is an inescapable component of the complete design cycle; however, it is impractical for us to give full details of the processes to which control might be applied, because they cover chemical plants, electromechanical systems, robots, power generators, and so on. We thus emphasize the fundamental control engineering aspects that are common to all applications and we leave readers to complement this emphasis with process knowledge relevant to their particular problem. Thus, the book is principally aimed at the second ingredient of control engineering. Of course, we do give details of several real-world examples, so as to put the methods into a proper context. The central theme of this book is continuous-time control; however, we also treat digital control in detail, because most modern control systems will usually be implemented on some form of computer hardware. This approach inevitably led to a book of larger volume than originally intended, but one with the advantage of providing a comprehensive treatment within an integrated framework. Naturally, there remain specialized topics that are not covered in the book; however, we trust that we provide a sufficiently strong foundation so that the reader can comfortably turn to the study of appropriate complementary literature. Goals Thus, in writing this book we chose as our principal goals the following: providing accessible treatment of rigorous material selected with applicability in mind; giving early emphasis to design, including methods for dealing with fundamental trade-offs and constraints; providing additional motivation through substantial interactive web-based support; and demonstrating the relevance of the material through numerous industrial case studies. Indeed, the material in the book is illustrated by numerous industrial case studies with which the authors have had direct involvement. Most of these case studies were carried out, in collaboration with industry, by the Centre for Integrated Dynamics and Control (CIDAC) (a Commonwealth Special Research Centre) at the University of Newcastle. The projects that we have chosen to describe include the following: satellite tracking pH control control of a continuous casting machine sugar mill control distillation column control ammonia-synthesis plant control zinc coating-mass estimation in a continuous-galvanizing line BISRA gauge for thickness control in rolling mills roll-eccentricity compensation in rolling mills hold-up effect in reversing rolling mills flatness control in steel rolling vibration control Design is a complex process, one that requires judgment and iteration. The design problem normally is incompletely specified, sometimes is ill-defined, and many times is without solution. A key element in design is an understanding of those factors that limit the achievable performance. This naturally leads to a viewpoint of control design that takes account of these fundamental limitations. This viewpoint is a recurring theme throughout the book. Our objective is not to explore the full depth of mathematical completeness but instead to give enough detail so that a reader can begin applying the ideas as soon as possible. This approach is connected to our assumption that readers will have ready access to modern computational facilities, including the software package MATLAB-SIMULINK. This assumption allows us to put the emphasis on fundamental ideas rather than on the tools. Every chapter includes worked examples and problems for the reader. Overview of the Book The book is divided into eight parts. A brief summary of each of the parts is given here. Part I: The Elements This part covers basic continuous-time signals and systems and would be suitable for an introductory course on this topic. Alternatively, it could be used to provide review material before starting the study of control in earnest. Part II: SISO Control Essentials This part deals with basic single-input single-output (SISO) control, including classical proportional, integral and derivative (PID) tuning. This section, together with Part I, covers the content of many of the existing curricula for basic control courses. Part III: SISO Control Design This part covers design issues in SISO Control. We consider many of these ideas to be crucial to achieving success in practical control problems. In particular, we believe that the chapter dealing with constraints should be mentioned, if at all possible, in all introductory courses. Also, feedforward and cascade structures, which are covered in this part, are very frequently employed in practice. Part IV: Digital Computer Control This part covers material essential to the understanding of digital control. We go beyond traditional treatments of this topic by studying inter-sample issues. Part V: Advanced SISO Control This part could be the basis of a second course on control at an undergraduate level. It is aimed at the introduction of ideas that flow through to multi-input multi-output (MIMO) systems later in the book. Part VI: MIMO Control Essentials This part gives the basics required for a junior-level graduate course on MIMO control. In particular, this part covers basic MIMO system theory. It also shows how one can exploit SISO methods in some MIMO design problems. Part VII: MIMO Control Design This part describes tools and ideas that can be used in industrial MIMO design. In particular, it includes linear quadratic optimal control theory and optimal filtering. These two topics have major significance in applications. We also include a chapter on Model Predictive Control. We believe this to be important material, because of the widespread use of this technique in industrial applications. Part VIII: Advanced MIMO Control This final part of the book could be left for private study. It is intended to test the reader's understanding of the other material by examining advanced issues. Alternatively, instructors could use this part to extend parts VI and VII in a more senior graduate course on MIMO Control. Using this Book This is a comprehensive book on control system design that can be used in many different course patterns. If one adopts the book for an early course on control, then the unused material is excellent reference material for later use in practice or for review. If one uses the book for a later course, then the early material gives an excellent summary of the basic building blocks on which the subject rests. The book can be used for many different course patterns. Some suggested patterns are outlined as follows: (i) Signals and Systems This would be taught from Part I of the book. (ii) Basic Control Theory This would typically be taught for Part II of the book, together with some material for Part I (depending on the student's prior exposure to signals and systems) and some material from Part III. In particular, the chapter on design limitations (Chapter 8) requires only elementary knowledge of Laplace Transforms and gives students an understanding of those issues which limit achievable performance. This is an extremely important ingredient in all real-world control design problems. Also, Chapter 11 which deals with constraints is very important in practice. Finally, the ideas of feedforward and cascade architectures that are covered in Chapter 10 are central to solving real-world design problems. (iii) Digital Control This can be taught from Part IV. Indeed, we feel our treatment here is better focused on applications than many of the traditional treatments because of the emphasis we place on intersample behavior. In the various courses taught by the authors of this book some of the material on digital control is typically included in the Basic Control Theory Course. This is possible because the students are well prepared having taken a Signals and System course prior to the control course. (iv) Second Course on Control A second course on control typically includes an introduction to state space design, observers, and state-variable feedback. This material can be taught from Parts V to VII of the book. Part V is relatively straightforward and is intended to bridge the gap from single-input single-output systems (which are principally the focus of Parts I to IV) and multi-input multi-output systems (which are principally covered in Parts VI, VII, and VIII). We consider Chapter 22 on optimal control and filtering to be very important and have included in this chapter many real world design case studies. Also, Chapter 23 on Model Predictive Control is important as this technique is widely used in industrial control. Two of the authors (Goodwin and Salgado) have taught undergraduate and postgraduate courses of the type mentioned above, using draft versions of this book, in Australia and South America. Website We have created a comprehensive website to support the book. This website contains the following: Full Appendices (So that this material can be read at the same time as the printed text in the book.) Full Matlab Support (This can be downloaded and used to reproduce all of the designs in the book.) Interactive Java Laboratories (These illustrate the material in the book but can also be used for fun interaction.) Selected Solutions for Problems (This allows students to see how certain key problems can be solved. Of course instructors adopting the book will be sent a copy of the comprehensive solutions manual that covers every problem set in the book.) On-Line Forum (So that topics of general interest to control-system design can be raised and discussed.) An Errata Section (This is used to give details of any errors occurring in the book.) Extensive PowerPoint Slides (Approximately 2,500 slides are available for use with the book.) We see the use of this material as follows: For the Instructor We believe that the Matlab support and PowerPoint slides should be particularly helpful to an instructor. For example, it would be possible to teach the course entirely using the resources provided. Also, we have found that students enjoy using the Virtual Laboratories. These can be displayed in the classroom as part of a lecture or given to students to enhance their understanding of the material. For the Student We believe that the PowerPoint slides are an excellent and easily understood summary of the book which by-passes all unnecessary technicalities. Even if your instructor does not use these slides in his/her presentations, we consider that they are an excellent summary for study purposes. If you print them out and annotate them, then remembering the material should be easy. Also, students should enjoy the Java Applets. If you can understand the case studies covered by these applets then you will be well on the way to understanding this exciting subject. The website can be accessed at either of the following URLs: http://www.prenhall.com/goodwin and http://csd.newcastle.edu.au/control/ Alternatively, see the authors' home pages for a link. Also note that the website is under continuous development, so the resources provided will continue to grow and evolve as time proceeds. Newcastle, Australia Valparaiso, Chile Vienna, Austria Excerpted from Control System Design by Graham C. Goodwin, Stefan F. Graebe, Mario E. Salgado All rights reserved by the original copyright owners. Excerpts are provided for display purposes only and may not be reproduced, reprinted or distributed without the written permission of the publisher.

Table of Contents

Contents Overviewp. vii
Acknowledgementsp. xxi
Prefacep. xxiii
I The Elementsp. 1
Previewp. 3
1 The Excitement of Control Engineeringp. 5
1.1 Previewp. 5
1.2 Motivation for Control Engineeringp. 5
1.3 Historical Periods of Control Theoryp. 9
1.4 Types of Control-System Designp. 10
1.5 System Integrationp. 11
1.6 Summaryp. 18
1.7 Further Readingp. 19
2 Introduction to the Principles of Feedbackp. 21
2.1 Previewp. 21
2.2 The Principal Goal of Controlp. 21
2.3 A Motivating Industrial Examplep. 22
2.4 Definition of the Problemp. 27
2.5 Prototype Solution to the Control Problem via Inversionp. 29
2.6 High-Gain Feedback and Inversionp. 32
2.7 From Open- to Closed-Loop Architecturesp. 34
2.8 Trade-offs Involved in Choosing the Feedback Gainp. 36
2.9 Measurementsp. 36
2.10 Summaryp. 38
2.11 Further Readingp. 39
3 Modelingp. 41
3.1 Previewp. 41
3.2 The Raison d'etre for Modelsp. 41
3.3 Model Complexityp. 42
3.4 Building Modelsp. 44
3.5 Model Structuresp. 45
3.6 State Space Modelsp. 45
3.7 Solution of Continuous-Time State Space Modelsp. 49
3.8 High-Order Differential and Difference-Equation Modelsp. 50
3.9 Modeling Errorsp. 50
3.10 Linearizationp. 52
3.11 Case Studiesp. 57
3.12 Summaryp. 58
3.13 Further Readingp. 60
3.14 Problems for the Readerp. 61
4 Continuous-Time Signals and Systemsp. 65
4.1 Previewp. 65
4.2 Linear Continuous-Time Modelsp. 65
4.3 Laplace Transformsp. 66
4.4 Laplace Transform. Properties and Examplesp. 67
4.5 Transfer Functionsp. 70
4.6 Stability of Transfer Functionsp. 74
4.7 Impulse and Step Responses of Continuous-Time Linear Systemsp. 74
4.8 Poles, Zeros, and Time Responsesp. 76
4.9 Frequency Responsep. 85
4.10 Fourier Transformp. 92
4.11 Models Frequently Encounteredp. 97
4.12 Modeling Errors for Linear Systemsp. 99
4.13 Bounds for Modeling Errorsp. 103
4.14 Summaryp. 104
4.15 Further Readingp. 108
4.16 Problems for the Readerp. 110
II SISO Control Essentialsp. 117
Previewp. 119
5 Analysis of SISO Control Loopsp. 121
5.1 Previewp. 121
5.2 Feedback Structuresp. 121
5.3 Nominal Sensitivity Functionsp. 125
5.4 Closed-Loop Stability Based on the Characteristic Polynomialp. 127
5.5 Stability and Polynomial Analysisp. 128
5.6 Root Locus (RL)p. 134
5.7 Nominal Stability using Frequency Responsep. 138
5.8 Relative Stability: Stability Margins and Sensitivity Peaksp. 143
5.9 Robustnessp. 145
5.10 Summaryp. 150
5.11 Further Readingp. 152
5.12 Problems for the Readerp. 154
6 Classical PID Controlp. 159
6.1 Previewp. 159
6.2 PID Structurep. 159
6.3 Empirical Tuningp. 162
6.4 Ziegler-Nichols (Z-N) Oscillation Methodp. 162
6.5 Reaction Curve Based Methodsp. 166
6.6 Lead-Lag Compensatorsp. 170
6.7 Distillation Columnp. 171
6.8 Summaryp. 174
6.9 Further Readingp. 175
6.10 Problems for the Readerp. 176
7 Synthesis of SISO Controllersp. 179
7.1 Previewp. 179
7.2 Polynomial Approachp. 179
7.3 PI and PID Synthesis Revisited by using Pole Assignmentp. 187
7.4 Smith Predictorp. 189
7.5 Summaryp. 191
7.6 Further Readingp. 192
7.7 Problems for the Readerp. 193
III SISO Control Designp. 197
Previewp. 199
8 Fundamental Limitations in SISO Controlp. 201
8.1 Previewp. 201
8.2 Sensorsp. 202
8.3 Actuatorsp. 203
8.4 Disturbancesp. 206
8.5 Model-Error Limitationsp. 206
8.6 Structural Limitationsp. 207
8.7 An Industrial Application (Hold-Up Effect in Reversing Mill)p. 222
8.8 Remediesp. 225
8.9 Design Homogeneity, Revisitedp. 232
8.10 Summaryp. 232
8.11 Further Readingp. 235
8.12 Problems for the Readerp. 237
9 Frequency-Domain Design Limitationsp. 241
9.1 Previewp. 241
9.2 Bode's Integral Constraints on Sensitivityp. 242
9.3 Integral Constraints on Complementary Sensitivityp. 246
9.4 Poisson Integral Constraint on Sensitivityp. 249
9.5 Poisson Integral Constraint on Complementary Sensitivityp. 254
9.6 Example of Design Trade-offsp. 256
9.7 Summaryp. 259
9.8 Further Readingp. 260
9.9 Problems for the Readerp. 263
10 Architectural Issues in SISO Controlp. 265
10.1 Previewp. 265
10.2 Models for Deterministic Disturbances and Referencesp. 265
10.3 Internal Model Principle for Disturbancesp. 267
10.4 Internal Model Principle for Reference Trackingp. 271
10.5 Feedforwardp. 271
10.6 Industrial Applications of Feedforward Controlp. 279
10.7 Cascade Controlp. 281
10.8 Summaryp. 285
10.9 Further Readingp. 288
10.10 Problems for the Readerp. 289
11 Dealing with Constraintsp. 293
11.1 Previewp. 293
11.2 Wind-Upp. 294
11.3 Anti-Wind-up Schemep. 295
11.4 State Saturationp. 301
11.5 Introduction to Model Predictive Controlp. 306
11.6 Summaryp. 306
11.7 Further Readingp. 307
11.8 Problems for the Readerp. 309
IV Digital Computer Controlp. 315
Previewp. 317
12 Models for Sampled-Data Systemsp. 319
12.1 Previewp. 319
12.2 Samplingp. 319
12.3 Signal Reconstructionp. 321
12.4 Linear Discrete-Time Modelsp. 322
12.5 The Shift Operatorp. 322
12.6 Z-Transformp. 323
12.7 Discrete Transfer Functionsp. 324
12.8 Discrete Delta-Domain Modelsp. 328
12.9 Discrete Delta-Transformp. 331
12.10 Discrete Transfer Functions (Delta Form)p. 335
12.11 Transfer Functions and Impulse Responsesp. 336
12.12 Discrete System Stabilityp. 336
12.13 Discrete Models for Sampled Continuous Systemsp. 337
12.14 Using Continuous State Space Modelsp. 340
12.15 Frequency Response of Sampled-Data Systemsp. 342
12.16 Summaryp. 345
12.17 Further Readingp. 348
12.18 Problems for the Readerp. 349
13 Digital Controlp. 353
13.1 Previewp. 353
13.2 Discrete-Time Sensitivity Functionsp. 353
13.3 Zeros of Sampled-Data Systemsp. 355
13.4 Is a Dedicated Digital Theory Really Necessary?p. 357
13.5 Approximate Continuous Designsp. 358
13.6 At-Sample Digital Designp. 362
13.7 Internal Model Principle for Digital Controlp. 372
13.8 Fundamental Performance Limitationsp. 376
13.9 Summaryp. 380
13.10 Further Readingp. 381
13.11 Problems for the Readerp. 383
14 Hybrid Controlp. 387
14.1 Previewp. 387
14.2 Hybrid Analysisp. 387
14.3 Models for Hybrid Control Systemsp. 387
14.4 Analysis of Intersample Behaviorp. 391
14.5 Repetitive Control Revisitedp. 393
14.6 Poisson Summation Formulap. 394
14.7 Summaryp. 396
14.8 Further Readingp. 397
14.9 Problems for the Readerp. 398
V Advanced SISO Controlp. 403
Previewp. 405
15 SISO Controller Parameterizationsp. 407
15.1 Previewp. 407
15.2 Open-Loop Inversion Revisitedp. 407
15.3 Affine Parameterization: The Stable Casep. 408
15.4 PID Synthesis by using the Affine Parameterizationp. 418
15.5 Affine Parameterization for Systems Having Time Delaysp. 427
15.6 Undesirable Closed-Loop Polesp. 430
15.7 Affine Parameterization: The Unstable Open-Loop Casep. 438
15.8 Discrete-Time Systemsp. 446
15.9 Summaryp. 447
15.10 Further readingp. 451
15.11 Problems for the Readerp. 453
16 Control Design Based on Optimizationp. 457
16.1 Previewp. 457
16.2 Optimal Q (Affine) Synthesisp. 458
16.3 Robust Control Design with Confidence Boundsp. 464
16.4 Cheap Control Fundamental Limitationsp. 478
16.5 Frequency-Domain Limitations Revisitedp. 480
16.6 Summaryp. 482
16.7 Further Readingp. 483
16.8 Problems for the Readerp. 486
17 Linear State Space Modelsp. 491
17.1 Previewp. 491
17.2 Linear Continuous-Time State Space Modelsp. 491
17.3 Similarity Transformationsp. 492
17.4 Transfer Functions Revisitedp. 494
17.5 From Transfer Function to State Space Representationp. 496
17.6 Controllability and Stabilizabilityp. 498
17.7 Observability and Detectabilityp. 508
17.8 Canonical Decompositionp. 513
17.9 Pole-Zero Cancellation and System Propertiesp. 516
17.10 Summaryp. 519
17.11 Further Readingp. 521
17.12 Problems for the Readerp. 523
18 Synthesis Via State Space Methodsp. 527
18.1 Previewp. 527
18.2 Pole Assignment by State Feedbackp. 527
18.3 Observersp. 531
18.4 Combining State Feedback with an Observerp. 537
18.5 Transfer-Function Interpretationsp. 539
18.6 Reinterpretation of the Affine Parameterization of all Stabilizing Controllersp. 545
18.7 State Space Interpretation of Internal Model Principlep. 546
18.8 Trade-Offs in State Feedback and Observersp. 551
18.9 Dealing with Input Constraints in the Context of State-Estimate Feedbackp. 552
18.10 Summaryp. 553
18.11 Further Readingp. 555
18.12 Problems for the Readerp. 556
19 Introduction to Nonlinear Controlp. 559
19.1 Previewp. 559
19.2 Linear Control of a Nonlinear Plantp. 559
19.3 Switched Linear Controllersp. 564
19.4 Control of Systems with Smooth Nonlinearitiesp. 567
19.5 Static Input Nonlinearitiesp. 567
19.6 Smooth Dynamic Nonlinearities for Stable and Stably Invertible Modelsp. 568
19.7 Disturbance Issues in Nonlinear Controlp. 575
19.8 More General Plants with Smooth Nonlinearitiesp. 580
19.9 Nonsmooth Nonlinearitiesp. 583
19.10 Stability of Nonlinear Systemsp. 585
19.11 Generalized Feedback Linearization for nonstability-Invertible Plantsp. 595
19.12 Summaryp. 603
19.13 Further Readingp. 604
19.14 Problems for the Readerp. 607
VI MIMO Control Essentialsp. 609
Previewp. 611
20 Analysis of MIMO Control Loopsp. 613
20.1 Previewp. 613
20.2 Motivational Examplesp. 613
20.3 Models for Multivariable Systemsp. 615
20.4 The Basic MIMO Control Loopp. 624
20.5 Closed-Loop Stabilityp. 626
20.6 Steady-State Response for Step Inputsp. 630
20.7 Frequency-Domain Analysisp. 631
20.8 Robustness Issuesp. 641
20.9 Summaryp. 644
20.10 Further Readingp. 646
20.11 Problems for the Readerp. 648
21 Exploiting Siso Techniques in MIMO Controlp. 653
21.1 Previewp. 653
21.2 Completely Decentralized Controlp. 653
21.3 Pairing of Inputs and Outputsp. 657
21.4 Robustness Issues in Decentralized Controlp. 660
21.5 Feedforward Action in Decentralized Controlp. 662
21.6 Converting MIMO Problems to SISO Problemsp. 664
21.7 Industrial Case Study (Strip Flatness Control)p. 666
21.8 Summaryp. 670
21.9 Further Readingp. 671
21.10 Problems for the Readerp. 672
VII MIMO Control Designp. 675
Previewp. 677
22 Design Via Optimal Control Techniquesp. 679
22.1 Previewp. 679
22.2 State-Estimate Feedbackp. 679
22.3 Dynamic Programming and Optimal Controlp. 682
22.4 The Linear Quadratic Regulator (LQR)p. 685
22.5 Properties of the Linear Quadratic Optimal Regulatorp. 687
22.6 Model Matching Based on Linear Quadratic Optimal Regulatorsp. 692
22.7 Discrete-Time Optimal Regulatorsp. 695
22.8 Connections to Pole Assignmentp. 696
22.9 Observer Designp. 698
22.10 Linear Optimal Filtersp. 699
22.11 State-Estimate Feedbackp. 713
22.12 Transfer-Function Interpretationp. 713
22.13 Achieving Integral Action in LQR Synthesisp. 716
22.14 Industrial Applicationsp. 718
22.15 Summaryp. 730
22.16 Further Readingp. 733
22.17 Problems for the Readerp. 736
23 Model Predictive Controlp. 739
23.1 Previewp. 739
23.2 Anti-Wind-Up Revisitedp. 740
23.3 What is Model Predictive Control?p. 744
23.4 Stabilityp. 748
23.5 Linear Models with Quadratic Cost Functionp. 751
23.6 State Estimation and Disturbance Predictionp. 756
23.7 Rudder Roll Stabilization of Shipsp. 758
23.8 Summaryp. 762
23.9 Further Readingp. 763
23.10 Problems for the Readerp. 766
24 Fundamental Limitations in MIMO Controlp. 771
24.1 Previewp. 771
24.2 Closed-Loop Transfer Functionp. 772
24.3 MIMO Internal Model Principlep. 773
24.4 The Cost of the Internal Model Principlep. 773
24.5 RHP Poles and Zerosp. 774
24.6 Time-Domain Constraintsp. 775
24.7 Poisson Integral Constraints on MIMO Complementary Sensitivityp. 780
24.8 Poisson Integral Constraints on MIMO Sensitivityp. 782
24.9 Interpretationp. 783
24.10 An Industrial Application: Sugar Millp. 785
24.11 Nonsquare Systemsp. 796
24.12 Discrete-Time Systemsp. 800
24.13 Summaryp. 800
24.14 Further Readingp. 802
24.15 Problems for the Readerp. 804
VIII Advanced MIMO Controlp. 807
Previewp. 809
25 MIMO Controller Parameterizationsp. 811
25.1 Previewp. 811
25.2 Affine Parameterization: Stable MIMO Plantsp. 811
25.3 Achieved Sensitivitiesp. 813
25.4 Dealing with Model Relative Degreep. 813
25.5 Dealing with NMP Zerosp. 824
25.6 Affine Parameterization: Unstable MIMO Plantsp. 841
25.7 State Space Implementationp. 844
25.8 Summaryp. 847
25.9 Further Readingp. 848
25.10 Problems for the Readerp. 850
26 Decouplingp. 853
26.1 Previewp. 853
26.2 Stable Systemsp. 854
26.3 Pre- and PostDiagonalizationp. 861
26.4 Unstable Systemsp. 863
26.5 Zeros of Decoupled and Partially Decoupled Systemsp. 873
26.6 Frequency-Domain Constraints for Dynamically Decoupled Systemsp. 876
26.7 The Cost of Decouplingp. 878
26.8 Input Saturationp. 882
26.9 MIMO Anti-Wind-Up Mechanismp. 883
26.10 Summaryp. 891
26.11 Further Readingp. 893
26.12 Problems for the Readerp. 895
Appendices
A Notation, Symbols, and Acronyms
B Smith-McMillan Forms
B.1 Introduction
B.2 Polynomial Matrices
B.3 Smith Form for Polynomial Matrices
B.4 Smith-McMillan Form for Rational Matrices
B.5 Poles and Zeros
B.6 Matrix Fraction Descriptions (MFD)
C Results From Analytic Function Theory
C.1 Introduction
C.2 Independence of Path
C.3 Simply Connected Domains
C.4 Functions of a Complex Variable
C.5 Derivatives and Differentials
C.6 Analytic Functions
C.7 Integrals Revisited
C.8 Poisson and Jensen Integral Formulas
C.9 Application of the Poisson-Jensen Formula to Certain Rational Functions
C.10 Bode's Theorems
D Properties of Continuous-Time Riccati Equations
D.1 Solutions of the CTDRE
D.2 Solutions of the CTARE
D.3 The stabilizing solution of the CTARE
D.4 Convergence of Solutions of the CTARE to the Stabilizing Solution of the CTARE
D.5 Duality between Linear Quadratic Regulator and Optimal Linear Filter
E Matlab Support