Adaptive Systems in Control and Signal Processing 1995 (eBook)

Front Cover 1
Adaptive Systems in Control and Signal Processing 1995 2
Copyright Page 3
Table of Contents 6
Part I: PLENARY SESSIONS 12
Chapter 1. IDENTIFICATION FOR CONTROL 12
1. INTRODUCTION 12
2. IDENTIFICATION IN OPEN AND CLOSED LOOP 14
3. THE DUAL CONTROL APPROACH 15
4. OPTIMAL IDENTIFICATION DESIGN FOR CONTROL 17
5. MATCHING IDENTIFICATION AND CONTROL CRITERION 20
6. CONCLUSIONS 22
ACKNOWLEDGEMENTS 23
7. REFERENCES 23
Chapter 2. COMBINED IDENTIFICATION AND CONTROL: ANOTHER WAY 24
1. INTRODUCTION 24
2. A NEW CONTROLLER STRUCTURE 26
3. A GENERIC SCHEME FOR OPTIMAL POLEPLACEMENT CONTROLLERS 27
4. COMBINED mENTIFICATION AND CONTROL SCHEMES 28
5. COMPARISON OF THE DIFFERENT SCHEMES 31
6. ON THE GENERIC OPTIMAL CONTROLLER SCHEME 32
7. EXAMPLES FOR OFF-LINE ITERATIVE REGULATOR REFINEMENT 34
8. A WORST-CASE OPTIMAL INPUT DESIGN ALGORITHM FOR OFF-LINE CLCR IDENTIFICATION 36
9. EXAMPLES FOR CLCR IDENTIFICATION BASED ON OPTIMAL INPUT DESIGN 38
10. ADAPTIVE SOLUTION FOR THE ON-LINE ITERATIVE REGULATOR REFINEMENT 39
11. THE CONCEPT OF AN ADAPTIVE "TRIPLECONTROL" 39
12. ADAPTIVE EXAMPLES 40
13. CONCLUSIONS 40
14. REFERENCES 41
Chapter 3. NONLINEAR ADAPTIVE FILTERS: DESIGN AND APPLICATION 42
1. INTRODUCTION 42
2. FILTERS FOR NOISE REDUCTION 43
3. ADAPTIVE EQUALISATION 44
4. A CLASSIFICATION PROBLEM 44
5. THE MULTILAYER PERCEPTRON 45
6. THE VOLTERRA SERIES 47
7. THE RADIAL BASIS FUNCTION NETWORK 48
8. THE DECISION FEEDBACK EQUALISER 50
9. SIGNAL PREDICTION 51
10. CONCLUSIONS 52
11. ACKNOWLEDGEMENTS 52
12. REFERENCES 52
Chapter 4. ADAPTIVE PREDICTIVE CONTROL 54
1 INTRODUCTION 54
2 MODELS 55
3 COST FUNCTIONS, PERFORMANCE AND ROBUSTNESS 57
4 CONSTRAINTS 59
5 RECURSIVE LEAST SQUARES AND UDU 60
6 SIMULTANEOUS ESTIMATION OF MODELS 60
7 USING THE UDU METHOD 62
8 FIDDLE FACTORS 62
9 CONCLUSIONS 64
10 ACKNOWLEDGEMENTS 64
11 REFERENCES 64
Chapter 5. A KULLBACK-LEIBLER DISTANCE APPROACH TO SYSTEM IDENTIFICATION 66
1. INTRODUCTION 66
2. PARAMETER ESTIMATION AND PROBABILITY 67
3. KULLBACK-LEIBLER DISTANCE 67
4. PARAMETER ESTIMATION AND KULLBACK-LEIBLER DISTANCE 68
5. ASYMPTOTIC APPROXIMATION VIA LARGE DEVIATIONS 70
6. COPING WITH "BAD" DATA 72
7. COPING WITH "BAD" MODEL 74
8. MARKOV CHAINS 75
9. CONCLUDING REMARKS 76
ACKNOWLEDGMENT 77
REFERENCES 77
Part II: INVITED SESSION WEAK-DUALITY FOR ADAPTIVE CONTROL 78
Chapter 6. Adaptive dual control methods: An overview 78
1. INTRODUCTION 78
2. ADAPTIVE CONTROL 78
3. CLASSIFICATION OF CONTROLLERS 79
4. NON-DUAL ADAPTIVE CONTROLLERS 79
5. OPTIMAL DUAL CONTROLLERS 80
6. SUBOPTIMAL DUAL CONTROLLERS 80
7. WHEN TO USE DUAL CONTROL? 82
8. SUMMARY 82
9. REFERENCES 82
Chapter 7. ADAPTIVE CONTROL BY WORST-CASE DUALITY 84
1. INTRODUCTION 84
2. THE WORST-CASE DUAL-CONTROL PROBLEM 85
3. A POSTERIORI FINITE-TIME TUNING BY A SYNERGIC SCHEME 88
4. CONCLUSION 89
REFERENCES 89
Chapter 8.PARAMETRIC UNCERTAINTY AND CONTROL PERFORMANCE IN STOCHASTIC ADAPTIVE CONTROL 90
1. INTRODUCTION 90
2. SELF-TUNING 90
3. PARAMETRIC UNCERTAINTY AND PERFORMANCE 91
4. OPTIMALITY 92
5. CONCLUSION 93
6. REFERENCES 93
Chapter 9. FREQUENCY SELECTIVE WEAKLY-DUAL ADAPTIVE CONTROL 94
1. INTRODUCTION 94
2. DESCRIPTION OF THE SYSTEM 95
3. OUTLINE OF THE ADAPTIVE SCHEME 96
4. STABILITY AND PERFORMANCE 97
5. CONCLUSION 99
REFERENCES 99
Chapter 10. ADAPTIVE CONTROL WITH IMPROVED ASYMPTOTIC PERFORMANCE IN THE PRESENCE OF DETERMINISTIC DISTURBANCES 100
Abstract 100
1 Introduction 100
2 Problem statement 101
3 Reasons for estimation algorithm 102
4 Adaptive control 103
5 Conclusion 105
References 105
Part III: CASE STUDY SESSION MULTISTAGE FLASH SEAWATER DESAUNATION PLANT CONTROL 106
Chapter 11. SIMULATION AIDED DESIGN AND DEVELOPMENT OF AN ADAPTIVE SCHEME WITH OPTIMALLY TUNED PID CONTROLLER FOR A LARGE MULTISTAGE FLASH SEAWATER DESALINATION PLANT - PART I: 106
1. INTRODUCTION AND PREAMBLE 106
2. MODELLING AND SIMULATION 108
3. CONCLUSION AND DISCUSSION ON FURTHER WORK 111
REFERENCES 111
Chapter 12. SIMULATION AIDED DESIGN AND DEVELOPMENT OF AN ADAPTIVE SCHEME WITH OPTIMALLY TUNED PID CONTROLLER FOR A LARGE MULTISTAGE FLASH SEA WATER DESALINATION PLANT - PART II: 112
1. INTRODUCTION 112
2. MODEL APPROXIMATION FOR PID CONTROL DESIGN 113
3. PROBLEM STATEMENT AND METHOD OF APPROACH 113
4. APPLICATION OF THE PRESENT METHOD 114
5. OPTIMAL PID TUNING WITH FODT APPROXIMATED PLANT MODELS 114
REFERENCES 114
Chapter 13. SIMULATION AIDED DESIGN AND DEVELOPMENT OF AN ADAPTIVE SCHEME WITH OPTIMALLY TUNED PID CONTROLLER FOR A LARGE MULTISTAGE FLASH SEAWATER DESALINATION PLANT - PART III: 118
1. INTRODUCTION 118
2. PID CONTROL SYSTEM SIMULATION AND OPTIMIZATION WITH UNREDUCED PLANT MODEL IN NONPARAMETRIC FORM 119
3. PARAMETER SCHEDULING SCHEME FOR A RANGE OF OPERATING CONDITIONS 121
4. CONCLUSIONS AND DIRECTIONS FOR FUTURE WORK 123
REFERENCES 123
Part IV: TECHNICAL SESSIONS ADVANCED TRACKING AND FORGETTING TECHNIQUES 124
Chapter 14. OPTIMISATION OF SET-POINT TRANSITION IN COMBINED CYCLE POWER PLANTS USING PREDICTIVE CONTROL TECHNIQUES 124
1. INTRODUCTION : A GENERIC COMBINED CYCLE POWER PLANT STRUCTURE AND A SIMULATION MODEL 124
2. THE TASK OF PREDICTIVE CONTROL 126
3. IMPLEMENTATION ISSUES 126
4. SIMULATION RESULTS 128
5. CONCLUSIONS 129
ACKNOWLEDGEMENTS 129
REFERENCES 129
Chapter 15. APPROXIMATE ARX MODEL ESTIMATION FOR JACKETING ADAPTIVE SYSTEMS 130
1. INTRODUCTION 130
2. THEORY OVERVIEW 131
3. POOLING FOR ARX MODEL 131
4. EXPERIMENTS 132
5. CONCLUSIONS 135
REFERENCES 135
Chapter 16. DISTRIBUTION OF THE RLS-ESTIMATOR IN A TIMEVARYING AR(l)-PROCESS. 136
1 INTRODUCTION 136
2 DEFINITIONS 136
3 DENSITY FUNCTION 137
4 MOMENTS 138
5 COMPUTATIONS 138
6 CONCLUSIONS 141
7 REFERENCES 141
Chapter 17. A COMPARISON OF IDENTIFICATION ALGORITHMS FOR RAPIDLY TIME-VARYING PARAMETERS ON A REAL PROCESS 142
1. INTRODUCTION 142
2. PARAMETER ESTIMATION VIA RLS 142
3. METHODS BASED ON .. (t) 143
4. METHODS BASED ON THE ESTIMATION e(t). 143
5. APPLICATION TO A REAL PLANT 144
6. CONCLUSIONS 147
7. ACKNOWLEDGMENTS 147
8. REFERENCES 147
Chapter 18. TIME-VARYING STABILIZED FORGETTING FOR RECURSIVE LEAST SQUARES IDENTIFICATION 148
1. INTRODUCTION 148
2. TIME-VARYING STABILIZED LS ESTIMATORS 148
3. STABILITY PROPERTIES 149
4. DETERMINISTIC PARAMETER CONVERGENCE PROPERTIES 151
5. EXTENSIONS 153
6. CONCLUSIONS 153
7. REFERENCES 153
Chapter 19. DYNAMICAL PROPERTIES OF THE RECURSIVE MAXIMUM LIKELYHOOD ALGORYTHM FOR FREQUENCY ESTIMATION 154
1. INTRODUCTION 154
2. THE RMLN ALGORITHM 154
3. DYNAMICAL ANALISYS 155
4. CLOSED-LOOP SIMULATIONS 157
5. CONCLUSIONS 158
6. ACKNOWLEDGEMENTS 159
7. REFERENCES 159
Part V: ADAPTIVE FILTERING AND STATE ESTIMATION 160
Chapter 20. ADAPTIVE RECEDING HORIZON STATE ESTIMATION FOR NON LINEAR PROCESSES 160
1. INTRODUCTION 160
2. THE ADAPTIVE RECEDING HORIZON STATE ESTIMATION 160
3. PERFORMANCES OF THE A.R.H.S.E. METHOD ON A NON-LINEAR PROCESS 163
4. CONCLUSION 165
REFERENCES 165
Chapter 21. A NEW REDUCED-ORDER ADAPTIVE FILTER FOR STATE ESTIMATION IN HIGH DIMENSIONAL SYSTEMS 166
1. INTRODUCTION 166
2. PREMILINARY RESULTS 166
3. ASYMPTOTICAL ROAF. APPROXIMATIONS 167
4. ASYMPTOTICALLY OPTIMAL ROAF 168
5. NONLINEAR ROAF 168
6. COMPUTATION OF THE TRANSITION MATRIX 169
7. SIMULATION RESULTS 169
8. CONCLUSION 170
9. REFERENCES 170
Chapter 22. ADAPTIVE FILTERING WITH FICTITIOUS ERROR SURFACES TO ACHIEVE GLOBAL CONVERGENCE 172
1. INTRODUCTION 172
2. FICTITIOUS ERROR SURFACES 173
3. THE COMPOSITE GRADIENT ALGORITHM 175
4. SUMMARY 177
REFERENCES 177
Chapter 23. UNBIASED ESTIMATION OF A SINUSOID IN NOISE VIA NOTCH FILTERS 178
1. INTRODUCTION AND PROBLEM POSITION 178
2. A MIN-MAX PROCEDURE FOR UNBIASED FREQUENCY ESTIMATION 179
3. A SIMULATION EXAMPLE 182
4. CONCLUDING REMARKS 183
ACKNOWLEDGMENTS 183
REFERENCES 183
Chapter 24. A COMPOSITE OBSERVER STRUCTURE FOR ADAPTIVE FOURIER ANALYSIS1 184
I. INTRODUCTION 184
II. THE POLYPHASE DECOMPOSITION OF THE RECURSIVE DFT 185
III. THE NEW ADAPTIVE FOURIER ANALYZER 186
IV. CONCLUSIONS 188
REFERENCES 188
Chapter 25. Lp (1=p=8) BLIND ADAPTIVE DECONVOLUTION AND ITS APPLICATIONS 190
1. INTRODUCTION 190
2. PARAMETRIC MODELS AND UNIQUENESS OF Lp AND L« BLIND DECONVOLUTION 192
3. SAMPLE VERSION OF L8, BLIND DECONVOLUTION AND THE STRONG CONSISTENCY OF ESTIMATOR 194
4. ITERATIVE AGORITHM FOR L8 BLIND DECONVOLUTION AND SIMULATION EXAMPLES 195
REFERENCES 195
Part VI: ADAPTIVE CONTROL APPLICATIONS 196
Chapter 26. DESIGN OF A MULTIVARIABLE STATE-SPACE ADAPTIVE CONTROLLER AND ITS APPLICATION TO A TURBO-GENERATOR PILOT PLANT 196
1. INTRODUCTION 196
2. PROCESS MODEL AND IDENTIFICATION 197
3. ADAPTIVE OPTIMAL LINEAR QUADRATIC CONTROLLER DESIGN 199
4. THE PILOT PLANT TURBO-GENERATOR 199
5. IMPLEMENTATION AND RESULTS 200
6. CONCLUSIONS 200
ACKNOWLEDGEMENT 201
REFERENCES 201
Chapter 27. MAINSTEAM TEMPERATURE RAISING CONTROL FOR A THERMAL POWER PLANT VIA MRACS BASED ON A QUICK IDENTIFICATION METHOD 202
1. INTRODUCTION 202
2. MODELLING OF SUPER-HEATER SYSTEM 203
3. A QUICK SYSTEM IDENTIFICATION METHOD 204
4. ADAPTIVE CONTROL 205
5. SIMULATION STUDIES 206
6. CONCLUSIONS 207
7. REFERENCES 207
Chapter 28. FREQUENCY BASED ADAPTIVE CONTROL OF SYSTEMS WITH ANTIRESONANCE MODES 208
1. INTRODUCTION 208
2. FREQUENCY BASED IMC 209
3. A CASE STUDY: LINEAR SYSTEM WITH ONE ANTIRESONANCE FREQUENCY 210
4. REAL SYSTEM WITH ANTIRESONANCE CHARACTERISTICS: A DISTRIBUTED SOLAR COLLECTOR FIELD 211
5. CONCLUSIONS 213
ACKNOWLEDGEMENTS 213
REFERENCES 213
APPENDIX A 213
Chapter 29. REALISTIC MODEL-BASED ADAPTIVE TEMPERATURE CONTROL OF BATCH REACTORS 214
1. INTRODUCTION 214
2. THE REACTOR SYSTEM 215
3. ADAPTIVE ALGORITHM FOR THE QUICK HEAT-UP OF THE REACTOR 215
4. SIMULATION AND PHYSICAL STUDY OF THE ALGORITHM 218
5. CONCLUSIONS 219
ACKNOWLEDGMENTS 219
NOTATION 219
REFERENCES 219
Chapter 30. ADAPTIVE PREDICTIVE CONTROL OF A CLASS OF NONLINEAR SYSTEMS A CASE STUDY 220
1. INTRODUCTION 220
2. BRIEF DESCRIPTION OF THE NONLINEAR DISCRETE TIME MODEL 221
3. THE ADAPTIVE PREDICTIVE CONTROL 221
4. APPLICATION TO A HEAT EXCHANGER 223
5. CONCLUSION 225
REFERENCES 225
Chapter 31. IMPROVED SCHEME OF ADAPTIVE POLE-ASSIGNMENT CONTROL FOR PNEUMATIC SERVO SYSTEM 226
1. INTRODUCTION 226
2. CONSTRUCTION OF THE PNEUMATIC SERVO SYSTEM 227
3. CONVENTIONAL DESIGN SCHEME 227
4. IMPROVED DESIGN SCHEME 228
5. EXPERIMENTAL RESULTS 229
6. CONCLUSION 229
REFERENCES 229
Chapter 32. A GLOBALLY CONVERGENT ROBUST CONTROLLER FOR ROBOT MANIPULATOR 232
1. INTRODUCTION 232
2. PROBLEM FORMULATION 232
3. ROBUST TRACKING CONTROL SCHEME 233
4. MODIFICATION FOR DISTURBANCE 234
5. EXAMPLE 235
6. CONCLUSION 236
7. REFERENCES 236
Chapter 33. A LYAPUNOV-STABLE ADAPTIVE SCHEME FOR FORCE REGULATION AND MOTION CONTROL OF ROBOT MANIPULATORS 238
1. INTRODUCTION 238
2. MODELLING 238
3. CONTROL DESIGN 239
4. STABILITY PROOF 240
5. JOINT SPACE IMPLEMENTATION 241
6. CONCLUSIONS 243
REFERENCES 243
Part VII: NEURAL NETWORKS 244
Chapter 34. A COMPARISON BETWEEN RBF NETWORKS AND CLASSICAL METHODS FOR IDENTIFICATION OF NONLINEAR DYNAMIC SYSTEMS 244
1. INTRODUCTION 244
2. CLASSICAL METHODS 245
3. RADIAL BASIS FUNCTION NETWORKS 246
4. TEST PROCESSES AND EXCITATION 247
5. RESULTS 248
6. CONCLUSIONS 249
REFERENCES 249
Chapter 35. NEURAL NETWORK ADAPTIVE CONTROL OF NONLINEAR PLANTS 250
1. INTRODUCTION 250
2. CONTROLLER STRUCTURE 251
3. CONTROL LAW 252
4. STABILITY 253
5. HEURISTIC ADAPTATION LAW 254
6. SIMULATIONS 254
7. CONCLUSIONS 255
ACKNOWLEDGEMENT 255
REFERENCES 255
Chapter 36. STABLE NONLINEAR ADAPTIVE CONTROL WITH GROWING RADIAL BASIS FUNCTION NETWORKS 256
1. INTRODUCTION 256
2. CONTROL OF AFFINE SYSTEMS 257
3. GROWING RBF NETWORK 257
4. NEURAL ADAPTIVE CONTROLLER 258
5. SIMULATION RESULTS 260
6. CONCLUSIONS 261
7. REFERENCES 261
Chapter 37. ROBUST IDENTIFICATION WITH NEURAL NETWORKS USING MULTIOBJECTIVE CRITERIA 262
1. INTRODUCTION 262
2. MULTIOBJECTIVE CRITERIA 263
3. METHOD OF INEQUALITIES 263
4. MODEL SELECTION 264
5. IDENTIFICATION ALGORITHM 265
6. EXPERIMENTAL RESULTS 266
7. CONCLUSIONS 267
8. REFERENCES 267
Chapter 38. A NEW LEARNING ALGORITHM FOR MULTI-LAYERED NEURAL NETWORKS BASED ON ADAPTIVE ALGORITHMS WITH IMPLEMENTATION BY HOPFIELD NETWORKS 268
1. INTRODUCTION 268
2. FEEDFORWARD NEURAL NETWORK ARCHITECTURE AND ITS STANDARD LEARNING ALGORITHM 269
3. A NEW LEARNING ALGORITHM AND ITS IMPLEMENTATION 269
4. PROPERTIES OF THE PROPOSED ALGORITHM 272
5. CONCLUSIONS 273
Acknowledgment 273
REFERENCES 273
Chapter 39. A CONVERGENCE ANALYSIS ON A MULTILAYERED NEURAL NETWORK USING A DISCRETE-TIME s -MODIFIED BACK PROPAGATION ALGORITHM 274
1. INTRODUCTION 274
2. LEARNING LAW 274
3. ANALYSIS 275
4. SIMULATION 276
5. CONCLUSION 277
6. ACKNOWLEDGEMENTS 277
REFERENCE 277
Chapter 40. NEURAL NETWORKS CAN BE TRAINED FASTER 280
1. INTRODUCTION 280
2. NEURAL NETWORKS 280
3. NUMERICAL METHODS 282
4. NUMERICAL EXAMPLES 284
5. CONCLUSION 285
6. REFERENCES 285
Part VIII: ADAPTIVE CONTROL 286
Chapter 41. TOWARDS FULLY PROBABILISTIC CONTROL DESIGN 286
1. Introduction 286
2. Basic elements 287
3. Control aim 287
4. Control aim in pdf terms 287
5. Optimization 287
6. Discussion 288
7. Linear Gaussian state space model 288
8. Conclusions 289
9. REFERENCES 289
Chapter 42. SELF-OPTIMALITY OF ADAPTIVE CONTROL SYSTEMS BASED ON THE CERTAINTY EQUIVALENCE PRINCIPLE 290
1. INTRODUCTION AND STATE OF THE ART 290
2. A GENERAL ADAPTIVE CONTROL SCHEME 291
3. ASYMPTOTIC PROPERTIES OF RLS ESTIMATES 292
4. CONVERGENCE ANALYSIS OF THE ADAPTIVE CONTROL SCHEME (RESULTS WITHOUT PROOFS) 293
5. CERTAINTY EQUIVALENCE APPLIED TO COMMON CONTROL STRATEGIES 294
ACKNOWLEDGEMENT 295
REFERENCES 295
Chapter 43. MRAC ALGORITHM FOR HIGH RELATIVE DEGREE PLANTS 296
1. INTRODUCTION 296
2. STANDARD MRAC ALGORITHM 297
3. STATE SPACE STRUCTURES IN CONTROL LAW 298
4. ZEROS ELIMINATION CONTROLLER 299
5. CONCLUSION 301
REFERENCES 301
Chapter 44. ADAPTIVE FEEDFORWARD CONTROL SCHEMES IN TIME-DOMAIN, FREQUENCY-DOMAIN AND WAVELET TRANSFORM DOMAIN 302
1. INTRODUCTION 302
2. FEEDFORWARD CONTROL PROBLEMS 303
3. TIME-DOMAIN APPROACH 303
4. FREQUENCY-DOMAIN APPROACH 304
5. WAVELET TRANSFORM DOMAIN SCHEME 305
6. SIMULATION AND EXPERIMENTAL STUDY 306
7. CONCLUSIONS 307
REFERENCES 307
Part IX: ROBUST ESTIMATION 308
Chapter 45. ESTIMATION OF APPROXIMATE MARKOV CHAINS 308
1. INTRODUCTION 308
2. THEORY 309
3. APPLICATION TO MC 311
4. ALGORITHMIC SUMMARY 312
5. ILLUSTRATIVE EXAMPLE 312
6. CONCLUSIONS 313
7. REFERENCES 313
Chapter 46. DECENTRALIZED MODEL REFERENCE ADAPTIVE CONTROL SYSTEM BASED ON ROBUST HIGH-ORDER ESTIMATOR 314
1. INTRODUCTION 314
2. PROBLEM STATEMET 315
3. CONTROL STRUCTURE 316
4. DESIGN OF FIXED COMPENSATOR 317
5. ROBUST HIGH-ORDER ESTIMATOR AND STABILITY ANALYSIS 318
6. CONCLUSIONS 319
REFERENCES 319
Chapter 47. A H8-NORM BOUNDED LEAST-SQUARES ALGORITHM 320
1. INTRODUCTION 320
2. PROBLEM DESCRIPTION 320
3. SOLUTION TO THE SUB-OPTIMAL PROBLEM 321
4. BOUNDS ON PARAMETER ERRORS 324
5. SUMMARY AND CONCLUSIONS 325
ACKNOWLEDGEMENTS 325
6. REFERENCES 325
Chapter 48. RECURSIVE INCREMENTAL LEAST SQUARES ESTIMATION ALGORITHM 326
1. INTRODUCTION 326
2. RECURSIVE INCREMENTAL LEAST SQUARES 327
3. ROBUST ESTIMATION 328
4. ESTIMATOR PROPERTIES 329
5. TRACKING SPEED AND DISTURBANCE ATTENUATION 331
6. CONCLUSIONS 331
7. REFERENCES 331
Part X: ROBUSTNESS OF ADAPTIVE CONTROLLERS 332
Chapter 49. ROBUSTNESS OF LQ SELF-TUNING CONTROLLER FOR NON-MINIMUM PHASE SYSTEMS 332
1. INTRODUCTION 332
2. THE FIXED LQ SCHEME 333
3. THE ERROR EQUATION 333
4. THE PARAMETER ESTIMATOR 335
5. STABILITY RESULTS 335
6. CONCLUSIONS 337
REFERENCES 337
Chapter 50. ON THE USE OF THE CONCEPT OF ROBUST STRICTLY POSITIVE REALNESS IN REDUCED ORDER ADAPTIVE CONTROL 338
1. INTRODUCTION 338
2. THE CONTROL PROBLEM 339
3. THE ADAPTIVE CASE 341
4. CONCLUSIONS 342
REFERENCES 343
APPENDIX A 343
Chapter 51. THE EFFECT OF DESIGN PARAMETERS ON ROBUST PERFORMANCE 344
1. INTRODUCTION 344
2. UNCERTAIN MODEL OF HEAT EXCHANGER NETWORKS 345
3. ROBUST ANALYSIS USING L8 SIGNAL NORM 346
4. THE EFFECT OF DESIGN PARAMETERS ON THE ROBUST PERFORMANCE 347
5. HEAT EXCHANGER CELL EXAMPLE 348
6. CONCLUSION 349
7. ACKNOWLEDGEMENT 349
8. REFERENCES 349
Chapter 52. SUBOPTIMAL ELLIPSOIDAL BOUNDING FOR SIMPLE ROBUST CONTROL IN SELF-TUNING ROBUST CONTROL 350
1. INTRODUCTION 350
2. ELLIPSOIDAL BOUNDING AND ROBUST CONTROL 350
3. ELLIPSOIDAL BOUNDING CRITERION FOR ROBUST CONTROL 352
4. CONCLUSIONS 354
APPENDIX A. CALCULATION OF ROBUST CONTROLLER FOR THE EXAMPLE PROCESS 354
APPENDIX B. CALCULATION OF OPTIMAL q FOR THE SCE-ALGORITHM 355
REFERENCES 355
Chapter 53. FINITE-TIME SELF-TUNING CONTROL BY MINIMAX ESTIMATORS AND AN UNCERTAINTY PRINCIPLE 356
1. INTRODUCTION 356
2. SOME INTRODUCTORY EXAMPLES 357
3. EVALUATION OF PERFORMANCE FOR SECOND ORDER MODELS. 357
4. THE UNCERTAINTY PRINCIPLE 360
5. NUMERICAL EVALUATION OF GUARANTEED SELF-TUNING PERFORMANCE 360
6. CONCLUSION 361
REFERENCES 361
Part XI: INTELUGENT TUNING 362
Chapter 54. HOW TO INCREASE ROBUSTNESS OF PID REGULATORS 362
1. INTRODUCTION 362
2. ITERATIVE CONTROL DESIGN APPROACHES 362
3. A CATAMARAN APPROACH TO ADAPTIVE CONTROL 363
4. A PRACTICAL ROBUST PID TUNING PROCEDURE 365
5. A RECURSIVE OPEN-LOOP INPUT DESIGN FOR CLCR roENTIHCATION 366
7. CONCLUSIONS 368
8. REFERENCES 368
Chapter 55. AUTO-TUNING OF DIGITAL PID CONTROLLERS USING RECURSIVE IDENTIFICATION 370
1. INTRODUCTION 370
2. ZIEGLER-NICHOLS PID CONTROLLERS DESIGN 371
3. POLE PLACEMENT PID CONTROLLERS DESIGN 373
4. MATLAB-TOOLBOX ATCPID 374
5. CONCLUSIONS 374
ACKNOWLEDGMENTS 375
REFERENCES 375
Chapter 56. A PID INSTRUMENT WITH SELF-TUNING 376
1. INTRODUCTION 376
2. SPECIFICATIONS 377
3. NOISE MONITORING 378
4. PRETUNE 378
5. PI CONTROLLER SETTINGS 379
6. FINE TUNE 380
7. CONCLUSIONS 381
REFERENCES 381
Chapter 57. SMART CONTROLLER FOR PNEUMATIC ACTUATOR 382
1. INTRODUCTION 382
2. EXPERIMENTAL SYSTEM AND MODEL 382
3. LINEARIZATION OF THE PLANT MODEL 383
4. CONTROL SYSTEM DESIGN 384
5. EXPERIMENTAL RESULTS 386
6. CONCLUSION 387
REFERENCES 387
Chapter 58. A NOVEL RELAY AUTO-TUNING TECHNIQUE FOR PROCESS WITH INTEGRATION 388
1. INTRODUCTION 388
2. RELAY WITH DC BIAS 388
3. A NOVEL RELAY AUTO-TUNING TECHNIQUE FOR PROCESS WITH INTEGRATION 390
4. EXPERIMENT ON A LEVEL CONTROL SYSTEM 390
5. CONCLUSION 392
6. REFERENCES 392
Chapter 59. SELFTUNING CONTROLLER ON THE PLC 394
1. INTRODUCTION 394
2. THEORETICAL BACKGROUND 395
3. IMPLEMENTATION OF THE SELFTUNING PROCEDURE 396
4. APPLICATION ON A HYDRAULIC PLANT 397
5. ROBUSTNESS ISSUES 398
6. CONCLUSION 399
REFERENCES 399
Part XII: NONUNEAR ADAPTIVE CONTROL SYSTEMS 400
Chapter 60. GH8 Self-tuning Control for Linear and NonLinear Systems 400
1. INTRODUCTION 400
2. STRUCTURE OF NON-LINEAR SELFTUNING CONTROL 400
3. NON-LINEAR SYSTEM IDENTIFICATION 401
4. NONLINEAR GH8 SELF-TUNING CONTROL 401
5. CASE STUDY 403
6. CONCLUSIONS 404
REFERENCES 404
Chapter 61. SELF-TUNING VSS-TYPE CONTROL FOR HAMMERSTEIN SYSTEMS: A GENERAL PREDICTIVE APPROACH. 406
1. INTRODUCTION 406
2. MINIMUM VARIANCE (MV) CONTROL 407
3. VSS SELF TUNING CONTROL 408
4. RESULTS 409
5. CONCLUSIONS 411
REFERENCES 411
Chapter 62. ADAPTIVE PREDICTIVE CONTROL OF NONLINEAR DYNAMIC PROCESSES 412
1. INTRODUCTION 412
2. PREDICTIVE CONTROL STRATEGY 412
3. SIMPLE NONLINEAR PROCESS MODELS AND THEIR PREDICTIVE FORMS 413
4. CONTROL STRATEGY 414
5. ADAPTIVE CONTROL 414
6. SIMULATION RESULTS 415
REFERENCES 417
Chapter 63. ADAPTIVE NONLINEAR CONTROLLER FOR CURRENT-CONTROLLED INDUCTION MOTOR 418
1. INTRODUCTION 418
2. ADAPTIVE TRACKING CONTROL FOR A SPECIAL CLASS OF NONLINEAR SYSTEMS 419
3. INDUCTION MOTOR MODEL 419
4. ADAPTIVE TRACKING CONTROLLERS FOR INDUCTION MOTOR 420
5. NUMERICAL SIMULATION OF THE ADAPTIVE CONTROLLER 420
6. ASPECTS OF ADAPTIVE CONTROLLER PRACTICAL APPLICATION 421
7. CONCLUSIONS 422
APPENDIX A 423
APPENDIX B 423
REFERENCES 423
Chapter 64. FEEDBACK LINEARISABILITY OF A NONLINEAR HEAT EXCHANGER 424
1. INTRODUCTION 424
2. SYSTEM MODELLING 424
3. FEEDBACK LINEARISATION 425
4. FEEDBACK LINEARISATION OF HEAT EXCHANGER MODEL 426
5. EXAMPLE 428
6. CONCLUSION 429
References 429
Part XIII: DESIGN OF CONTROLLERS FOR ADAPTIVE SYSTEMS 430
Chapter 65. DUAL VERSION OF DIRECT ADAPTIVE POLE PLACEMENT CONTROLLER 430
1. INTRODUCTION 430
2. DESIGN OF ADAPTIVE POLE PLACEMENT CONTROLLER WITH STANDARD APPROACH 431
3. DESIGN OF DIRECT ACTIVE ADAPTIVE POLE PLACEMENT CONTROLLER 432
4. SIMULATED EXAMPLES 433
5. COMPARISON OF CONTROLLERS BASED ON STANDARD AND ACTIVE ADAPTIVE APPROACHES 435
6. CONCLUSIONS 435
7. ACKNOWLEDGEMENT 435
8. REFERENCES 435
Chapter 66. A SIMPLE POLE-ASSIGNMENT SCHEME FOR DESIGNING MULTIVARIABLE SELF-TUNING CONTROLLERS 436
1. INTRODUCTION 436
2. A SIMPLE POLE-ASSIGNMENT SELF-TUNING CONTROLLER 436
3. CONVERGENCE ANALYSIS 438
4. SIMULATION EXAMPLES 440
5. CONCLUSIONS 441
References 441
Chapter 67. AN ADAPTIVE VSS REGULATOR FOR MULTIVARIABLE NONMINIMUM-PHASE SYSTEMS BASED ON DOUBLY COPRIME FACTORIZATION 442
1. INTRODUCTION 442
2. PROBLEM STATEMENT 443
3. BASIC CONFIGURATION 443
4. DESIGN METHODOLOGY FOR A KNOWN SYSTEM 444
5. ADAPTIVE CONTROL 446
6. CONCLUSIONS 447
REFERENCES 447
Chapter 68. SELF-TUNING CONTROL OF LUMPED INPUT AND DISTRIBUTED OUTPUT SYSTEMS 448
1. INTRODUCTION 448
2. REAL LUMPED INPUT AND DISTRIBUTED OUTPUT SYSTEMS 449
3. LUMPED INPUT AND DISTRIBUTED OUTPUT PREDICTOR 449
4. DISTRIBUTED PARAMETER SELF-TUNING SYSTEM OF CONTROL 451
5. CONCLUSION 453
6. REFERENCES 453
Chapter 69. A CACE Tool for Analysis and Design of Adaptive Control Systems 454
1. Introduction 454
2. Program and Data Structure for an Adaptive Controller 455
3. Implementation in MATLAB 456
4. Example of Simulating an Adaptive Control System 458
5. Conclusion 459
6. Acknowledgement 459
7. References 459
Part XIV: IDENTIFICATION ALGORITHMS FOR ADAPTIVE CONTROL 460
Chapter 70. IDENTIFICATION AND DYNAMIC WEIGHTS FOR LQG CONTROL WITH INTEGRAL ACTION 460
1. INTRODUCTION 460
2. IDENTIFICATION FOR OFFSET-FREE LQG CONTROL WITH INTEGRAL ACTION 460
3. LQG CONTROL WITH DYNAMIC WEIGHTS 463
6. CONCLUSIONS 465
REFERENCES 465
Chapter 71. ROBUST ESTIMATION IN THE PRESENCE OF NOISE UNCERTAINTY AND UNMODELED DYNAMICS 466
1. INTRODUCTION 466
2. PROBLEM FORMULATION 467
3. ROBUST PARAMETER ESTIMATION 468
4. CONCLUSIONS 471
REFERENCES 471
Chapter 72. TEMPLATE FUNCTIONS BASED ESTIMATORS FOR ADAPTIVE CONTROL 472
1. INTRODUCTION 472
2. SYSTEM DESCRIPTION 472
3. THE TEMPLATE FUNCTION METHODS 473
4. THE EXTENDED TEMPLATE FUNCTION ESTIMATOR 474
5. THE RECURSIVE TEMPLATE FUNCTION ESTIMATOR 475
6. CONCLUSION 477
7. APPENDIX 477
8. REFERENCES 477
Chapter 73. SET POINT AND IDENTIFIABILITY IN THE CLOSED LOOP WITH MINIMUM VARIANCE CONTROLLER1 478
1. INTRODUCTION 478
2. MINIMUM VARIANCE SELF-TUNING CONTROL 479
3. SOME QUESTIONS OF IDENTIFIABILITY 480
4. THE LOW EXCITATION PROBLEM 481
5. EXAMPLE 481
6. CONCLUSIONS 482
REFERENCES 482
Chapter 74. Impulse response identification using multiresolution analysis 484
1 Introduction 484
2 Conventional identification method for DTIRM 485
3 Multiresolution analysis of CTIR 485
4 Identification algorithm 486
5 Simulation results 487
6 Conclusions 488
References 488
AUTHOR INDEX 490