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1 WHAT IS ADAPTIVE CONTROL? 1

1.1 Introduction 1

1.2 Linear Feedback 3

1.3 Effects of Process Variations 9

1.4 Adaptive Schemes 19

1.5 The Adaptive Control Problem 24

1.6 Applications 27

1.7 Conclusions 33

Problems 34

References 38

2 REAL-TIME PARAMETER ESTIMATION 41

2.1 Introduction 41

2.2 Least Squares and Regression Models 42

2.3 Estimating Parameters in Dynamical Systems 56

2.4 Experimental Conditions 63

2.5 Simulation of Recursive Estimation 71

2.6 Prior Information 78

2.7 Conclusions 82

Problems 82

References 87

3 DETERMINISTIC SELF-TUNING REGULATORS 90

3.1 Introduction 90

3.2 Pole Placement Design 92

3.3 Indirect Self-tuning Regulators 102

3.4 Continuous-Time Self-tuners 109

3.5 Direct Self-tuning Regulators 112

3.6 Disturbances with Known Characteristics 121

3.7 Conclusions 128

Problems 129

References 135

4 STOCHASTIC AND PREDICTIVE SELF-TUNING REGULATORS 137

4.1 Introduction 137

4.2 Design of Minimum-Variance and Moving-Average Controllers 137

4.3 Stochastic Self-tuning Regulators 146

4.4 Unification of Direct Self-tuning Regulators 156

4.5 Linear Quadratic STR 164

4.6 Adaptive Predictive Control 168

4.7 Conclusions 178

Problems 179

References 181

5 MODEL-REFERENCE ADAPTIVE SYSTEMS 185

5.1 Introduction 185

5.2 TheMIT Rule 186

5.3 Determination of the Adaptation Gain 194

5.4 Lyapunov Theory 199

5.5 Design of MRAS Using Lyapunov Theory 206

5.6 Bounded-Input,Bounded-Output Stability 215

5.7 Applications to Adaptive Control 230

5.8 Output Feedback 235

5.9 Relations between MRAS and STR 243

5.10 Nonlinear Systems 245

5.11 Conclusions 255

Problems 256

References 260

6 PROPERTIES OF ADAPTIVE SYSTEMS 263

6.1 Introduction 263

6.2 Nonlinear Dynamics 265

6.3 Adaptation of a Feedforward Gain 274

6.4 Analysis of Indirect Discrete-Time Self-tuners 280

6.5 Stability of Direct Discrete-Time Algorithms 293

6.6 Averaging 299

6.7 Application of Averaging Techniques 306

6.8 Averaging in Stochastic Systems 319

6.9 Robust Adaptive Controllers 327

6.10 Conclusions 338

Problems 338

References 343

7.1 Introduction 348

7 STOCHASTIC ADAPTIVE CONTROL 348

7.2 Multistep Decision Problems 350

7.3 The Stochastic AdaptiveProblem 352

7.4 Dual Control 354

7.5 Suboptimal Strategies 362

7.6 Examples 365

7.7 Conclusions 370

Problems 371

References 372

8 AUTO-TUNING 375

8.1 Introduction 375

8.2 PID Control 376

8.3 Auto-tuning Techniques 377

8.4 Transient Response Methods 378

8.5 Methods Based on Relay Feedback 380

8.6 Relay Oscillations 385

Problems 388

8.7 Conclusions 388

References 389

9 GAIN SCHEDULING 390

9.1 Introduction 390

9.2 The Principle 391

9.3 Design of Gain-Scheduling Controllers 392

9.4 Nonlinear Transformations 398

9.5 Applications of Gain Scheduling 402

9.6 Conclusions 416

Problems 416

References 417

10 ROBUST AND SELF-OSCILLATING SYSTEMS 419

10.1 Why Not Adaptive Control? 419

10.2 Robust High-Gain Feedback Control 419

10.3 Self-oscillating Adaptive Systems 426

10.4 Variable-Structure Systems 436

Problems 442

10.5 Conclusions 442

References 445

11 PRACTICAL ISSUES AND IMPLEMENTATION 448

11.1 Introduction 448

11.2 Controller Implementation 449

11.3 Controller Design 458

11.4 Solving the Diophantine Equation 462

11.5 Estimator Implementation 465

11.6 Square Root Algorithms 480

11.7 Interaction of Estimation and Control 487

11.8 Prototype Algorithms 490

11.9 Operational Issues 493

11.10 Conclusions 494

Problems 496

References 497

12 COMMERCIAL PRODUCTS AND APPLICATIONS 499

12.1 Introduction 499

12.2 Status of Applications 500

12.3 Industrial Adaptive Controllers 503

12.4 Some Industrial Adaptive Controllers 506

12.5 Process Control 517

12.6 Automobile Control 527

12.7 Ship Steering 529

12.8 Ultrafiltration 534

12.9 Conclusions 541

References 542

13.1 Introduction 545

13 PERSPECTIVES ON ADAPTIVE CONTROL 545

13.2 Adaptive Signal Processing 546

13.3 Extremum Control 550

13.4 Expert Control Systems 554

13.5 Learning Systems 557

13.6 Future Trends 559

13.7 Conclusions 561

References 562

INDEX 565