Adaptive Systems in Control and Signal Processing 1992 (eBook)

Front Cover 1
Adaptive Systems in Control and Signal Processing 1992 4
Copyright Page 5
Table of Contents 10
IFAC SYMPOSIUM ON ADAPTIVE SYSTEMS IN CONTROL AND SIGNAL PROCESSING 1992 6
FOREWORD 8
CHAPTER 1. RECURSIVE PARAMETER ESTIMATION FOR ARBITRARY HIDDEN MARKOV MODELS 16
INTRODUCTION 16
EM AND ON-LINE PARAMETER ESTIMATION 16
RE-ESTIMATION OF STATE TRANSITION PROBABILITIES 17
RE-ESTIMATION OF OBSERVATION PROBABILITIES 18
CONCLUSION 19
REFERENCES 19
CHAPTER 2. MODEL REDUCTION IN RECURSIVE LEAST SQUARES IDENTIFICATION 20
1 INTRODUCTION 20
2 BASIC PRINCIPLES 21
3 REDUCTION WITH COMPLETE STRUCTURE ESTIMATION 22
4 REDUCTION WITH SIMPLIFIED STRUCTURE ESTIMATION 23
5 SIMULATION RESULTS 24
6 CONCLUSIONS 25
REFERENCES 25
CHAPTER 3. ON SIMULTANEOUS SYSTEM AND INPUT SEQUENCE ESTIMATION 26
1 Introduction 26
2 Problem Formulation 27
3 The MAP Estimate 27
4 A Practical Algorithm 28
5 IDENTIFIABILITY 29
6 AN APPLICATION 30
7 CONCLUSIONS 31
References 31
CHAPTER 4. DESIGN CRITERIA FOR ROBUST STRICT POSITIVE REALNESS IN ADAPTIVE SCHEMES 32
INTRODUCTION 32
PROBLEM FORMULATION AND PRELIMINARIES 32
SUB-OPTIMAL SOLUTIONS TO PR AND FD PROBLEMS FOR GENERAL ROOT LOCATION REGIONS 34
NUMERICAL EXAMPLES 35
CONCLUSIONS 37
ACKNOWLEDGEMENTS 37
REFERENCES 37
CHAPTER 5. ROBUST IDENTIFICATION FOR ADAPTIVE CONTROL: THE DYNAMIC HINKLEY-DETECTOR 38
INTRODUCTION 38
FROM THE HINKLEY-DETECTCR TO THE DYNAMIC HINKLEY-DETECTOR 38
DISCUSSION 42
REFERENCES 43
CHAPTER 6. PARAMETER ESTIMATION VIA FIXED LEAKAGE MODIFICATION SCHEME FOR A CLASS OF NONLINEAR SYSTEMS 44
1. INTRODUCTION 44
2. PRELIMINARIES 44
3. PARAMETER ESTIMATION WITH FIXED alpha*- MODIFIGATION SCHEME 46
4. CONCLUSION 48
REFERENCES 48
CHAPTER 7. TOWARDS REAL-TIME IMPLEMENTATION OF BAYESIAN PARAMETER ESTIMATION 50
INTRODUCTION 50
BAYESIAN ESTIMATION 51
NON-PARAMETRIC VIEW 51
COMPRESSION OF DATA 51
IDEA OF APPROXIMATION 52
SUMMARY OF APPROXIMATION 53
DISCRETE IMPLEMENTATION 53
ILLUSTRATIVE EXAMPLE 54
NETWORK IMPLEMENTATION 54
CONCLUDING REMARKS 54
REFERENCES 55
CHAPTER 8. ADAPTIVE PID DESIGN EXPLOITING PARTIAL PRIOR INFORMATION 56
1. Introduction 56
2. Plant versus Model Limitations 57
3. Robust PID Design 58
4. Adaptive PID Design 60
5. Adaptive PID Control with Prior Information 60
6. Conclusions 61
Acknowledgements 61
References 61
CHAPTER 9. IDENTIFICATION OF NONLINEAR STOCHASTIC GREY BOX MODELS: Theory, Implementation, and Experiences 62
1. Introduction 62
2. Review of Theory 62
3. Procedures and Tools 64
4. Case Study 1: Mould Level Control 65
5. Case Study 2: Strip Steel Rinsing 66
6. Conclusions 67
Acknowledgements: 67
References 67
CHAPTER 10. VALIDATION OF GREY BOX MODELS 68
1 Introduction 68
2 Likelihood based Test Procedures 69
3 Information Methods for Order Selection 69
4 Residual Analysis 70
5 Nonparametric Estimation and Bootstrap 71
6 Validation methods based on nonlinear techniques 72
7 Bayesian Methods 73
References 75
CHAPTER 11. SYSTEM IDENTIFICATION USING BONDGRAPHS 76
1 Choice of Model Structures 76
2 Bondgraph Modeling 76
3 Software Requirement for Merging Bondgraph Modeling and System Identification 77
4 The MaMiC System 77
5 BOND TOOL 79
6 Example 79
7 Intelligent Help 81
8 Summary and Conclusions 81
References 81
CHAPTER 12. BOND-GRAPH BASED ADAPTIVE CONTROL 82
1 Introduction 82
2 Modelling with Bond Graphs 82
3 Adaptive Model-Based Observer (MBO) Control 83
4 An Example: three coupled tanks 84
5 The System 84
6 The Model-Based Observer 84
7 Simulation 85
8 Conclusion 87
9 Acknowledgements 87
References 87
CHAPTER 13. OVERTRAINING, REGULARIZATION, AND SEARCHING FOR MINIMUM IN NEURAL NETWORKS 88
1 Introduction 88
2 Neural Networks as models of dynamical systems 88
3 Regularization and variance reduction 89
4 Terminating iterative search for the minimum is regularization 91
5 Modeling a hydraulic robot arm 92
6 Conclusions 93
References 93
CHAPTER 14. ON LETTING ADAPTIVE CONTROL BE WHAT IT IS: NONLINEAR FEEDBACK1 94
Abstract 94
1 Introduction 94
2 State Feedback Design 94
3 Output Feedback Design 96
4 Transient Performance Improvement 98
5 Conclusions 100
References 100
CHAPTER 15. ADAPTIVE CONTROL OF SYSTEMS WITH BACKLASH 102
1 Introduction 102
2 Backlash and Its Right Inverse 102
3 Parametrization 104
4 An Introductory Example 105
5 Adaptive Control Design 106
6 Conclusions 107
Acknowledgements 108
References 108
CHAPTER 16. SELF-TUNING STABILIZATION OF FEEDBACK LINEARIZABLE SYSTEMS1 110
Abstract 110
1 Introduction 110
2 Preliminaries 111
3 Robust stabilization 112
4 Self-tuning stabilization 113
References 115
CHAPTER 17. SELF-TUNING OUTPUT FEEDBACK STABILIZATION OF A CLASS OF NONLINEAR SYSTEMS1 116
Abstract 116
1 Introduction 116
2 Basic results 116
3 Self-tuning output back stabilization feedback stabilization 117
CHAPTER 18. MODEL REFERENCE ADAPTIVE CONTROL AND IDENTIFICATION FOR NONLINEAR SYSTEMS: METHODS AND APPLICATIONS 122
INTRODUCTION 122
MRAS DESIGN FOR LINEAR SYSTEMS 122
NONLINEAR MRAC USING ERROR-EQUATION METHOD 122
NONLINEAR MRAC USING THE PRODUCT-SPACE METHOD 124
CONCLUSIONS 126
REFERENCES 126
CHAPTER 19. SELF-TUNING CONTROL OF NONLINEAR SYSTEMS USING NONPARAMETRIC ESTIMATION 128
INTRODUCTION 128
CONTROL ALGORITHM 128
APPLICATIONS 129
CONCLUSION 131
REFERENCES 131
CHAPTER 20. APPLICATION OF AVERAGING METHOD FOR INTEGRO-DIFFERENTIAL EQUATIONS TO MODEL REFERENCE ADAPTIVE CONTROL OF PARABOLIC SYSTEMS1 134
I. INTRODUCTION 134
II.. AVERAGING METHOD FOR INTEGRODIFFERENTIAL EQUATIONS 134
III. DIRECT ADAPTIVE CONTROL OF PARABOLIC SYSTEMS 135
IV. ANALYSIS OF PARAMETER CONVERGENCE 137
V. CONCLUSIONS 139
REFERENCES 139
CHAPTER 21. APPLICATION OF PASSIVE SYSTEM APPROACH FOR ADAPTIVE HYBRID FORCE-POSITION CONTROL 140
1. Introduction 140
2. Modelization of constrained robot and its environnent 140
3. Force and Position control (frictionless contact) 141
4. CONCLUSION 145
REFERENCES 145
CHAPTER 22. ADAPTIVE SYSTEMS PERFORMANCE IN THE FREQUENCY DOMAIN 146
1. INTRODUCTION 146
2. FREQUENCY DOMAIN FIT THEME 146
3. BIAS 147
4. CONVERGENCE RATES 148
5. VARIANCE 149
6. GENERALIZATIONS TO OTHER CASES 150
7. CONCLUSIONS 151
REFERENCES 151
CHAPTER 23. A COMMENT ON "LEAKAGE" IN ADAPTIVE ALGORITHMS 154
1 Introduction Adaptive Parameter Estimation and Leakage 154
2 Leakage is Regularization 155
3 Regularization and variance reduction 155
4 Conclusions 157
References 158
CHAPTER 24. DIRECT ADAPTIVE CONTROL OF NONMINIMUM PHASE SYSTEMS WITH FAST CONVERGENCE 160
INTRODUCTION 160
CONTROLSTRUCTURE 160
DIRECT ADAPTIVE CONTROL SCHEME 161
COMPUTER SIMULATION 163
CONCLUSIONS 163
Acknowledgements 163
References 163
CHAPTER 25. ADAPTIVE STABILIZATION OF ONE-PARAMETER FAMILIES OF SISO LINEAR SYSTEMS1 166
Introduction 166
1. Parameterized Transfer Functions 166
2. Design Models Ed 167
3. Identifiers .I 168
4. Internal Regulators .I 168
5. Properties 169
Concluding Remarks 169
References 170
CHAPTER 26. ANALYSIS OF THE INCREMENTAL TUNER 172
1. INTRODUCTION 172
2. PROBLEM STATEMENT 173
3. DESIGN MOTIVATION 173
4. CLOSED LOOP ESTIMATION 174
5. INCREMENTAL CONTROLLER TUNING 174
6. AVERAGING ANALYSIS 175
7. CONCLUSION 177
8. REFERENCES 177
CHAPTER 27. STABLE INDIRECT ADAPTIVE CONTROL OF CONTINUOUS-TIME SYSTEMS WITH NO PRIORI KNOWLEDGE ON THE PARAMETERS 178
Abstract 178
1 Introduction 178
2 The adaptive pole placement problem 179
3 Loss of stabilizability: A simple example 180
4 The switched–excitation approach: A simple example 180
5 The switched excitation approach: general case 181
6 Conclusion 182
References 183
CHAPTER 28. SINGULARITY-FREE ADAPTIVE POLE PLACEMENT FOR 2nd ORDER SYSTEMS 184
1. INTRODUCTION 184
2. IDENTIFICATION OF SYSTEMS SUBJECT TO BOUNDED DISTURBANCES 185
3. ADAPTIVE POLE PLACEMENT 186
4. MODIFICATION OF THE ESTIMATES FOR SECOND ORDER SYSTEMS 186
5. CONCLUSION 189
REFERENCES 189
CHAPTER 29. ADAPTIVE STABILIZATION FOR 2nd ORDER CONTINUOUS-TIME SYSTEMS 190
1. INTRODUCTION 190
2. SYSTEM PARAMETER ESTIMATION 191
3. ADAPTIVE POLE PLACEMENT 192
4. CONVERGENCE ANALYSIS 194
5. CONCLUSION 195
REFERENCES 195
CHAPTER 30. SUPERMARTINGALE ANALYSIS OF MINIMUM VARIANCE ADAPTIVE CONTROL 196
Introduction 196
System Description and Notations 196
State Space Model 197
Stochastic Stability Analysis 198
Discussion and Conclusions 199
Appendix 200
References 201
CHAPTER 31. ADAPTIVE vs ROBUST CONTROL: INFORMATION BASED CONCEPTS 202
ABSTRACT 202
1. INTRODUCTION 202
2. ROBUST VS. ADAPTIVE SENSITIVITY MINIMIZATION 202
APPENDIX: Theorem 2.1 204
REFERENCES 205
CHAPTER 32. LOWER INFORMATION BOUNDS FOR AN ADAPTIVE CONTROL PROBLEM 206
1 Introduction 206
2 Problem Statement 206
3 Main Results 207
4 Discussion 208
5 Appendix 208
References 211
CHAPTER 33. MODEL REFERENCE ADAPTIVE CONTROL FOR NON-MINIMUM PHASE SYSTEM BY 2-DELAY FEEDBACK 212
INTRODUCTION 212
PROBLEM STATEMENT 212
DESCRIPTION OF 2-DELAY SAMPLING SYSTEM 213
ADAPTIVE CONTROL BY 2-DELAY FEEDBACK 214
SIMULATION RESULTS 216
CONCLUSION 216
REFERENCES 216
CHAPTER 34. ROBUST MODEL REFERENCE ADAPTIVE CONTROL IN THE PRESENCE OF PARASITICS 218
1. INTRODUCTION 218
2. STATEMENT OF THE PROBLEM 218
3. ROBUST DESIGN OF MRAC SYSTEM 219
4. STABILITY OF THE MRAC SYSTEM 220
5. SIMULATION RESULTS 222
6. CONCLUSION 223
REFERENCES 223
CHAPTER 35. MODEL REFERENCE ADAPTIVE CONTROL AND ADAPTIVE STABILITY AUGMENTATION 224
INTRODUCTION 224
CONCEPTS IN MODEL REFERENCE ADAPTIVE CONTROL. 225
ADAPTIVE STABILITY AUGMENTATION OF THE MODEL REFERENCE DESIGN. 226
DERIVATION OF THE STABILITY AUGMENTED MRAC ALGORITHM. 226
SIMULATION RESULTS 228
CONCLUSION 229
REFERENCES 229
CHAPTER 36. MULTIVARIABLE NYQUIST GENERALIZED PREDICTIVE CONTROL: AN HELICOPTER APPLICATION 230
NOTATIONS 230
INTRODUCTION 230
METHODOLOGY 230
APPLICATION 232
CONCLUSION 235
REFERENCES 235
CHAPTER 37. ADAPTIVE PREDICTIVE CONTROL OF ARMAX PLANTS WITH UNKNOWN DEADTIME 236
1 Introduction 236
2 Background 236
3 ARMAX plants 237
4 SIORHC algorithm 239
5 Simulation results 240
6 Conclusions 240
References 240
Appendix 241
CHAPTER 38. DESIGN OF DECENTRALIZED ADAPTIVE CONTROLLERS USING THE PRINCIPLE OF DOMINANT SUBSYSTEMS 242
INTRODUCTION 242
PROBLEM STATEMENT 242
CONCLUSIONS 246
REFERENCES 246
CHAPTER 39. ALGORITHM AND ROBUSTNESS FOR A MULTIVARIABLE IMPLICIT SELF-TUNING CONTROLLER 248
1. Introduction 248
2. System Description 249
3. The Implicit STC Algorithm 249
4. Parameter Identification 249
5. The Implicit Self-Tuning Algorithm 250
6. Stability Robustness 250
7. Simulation Study 251
8. Conclusions 252
9. Acknowledgements 252
References 252
CHAPTER 40. REDUCED PARAMETRIZATION FOR DISCRETE-TIME MULTIVARIABLE ADAPTIVE CONTROL 254
ABSTRACT 254
1 INTRODUCTION 254
2 SYSTEM DELAY STRUCTURE AND MATCHABLE MODELS 254
3 SOME PROPERTIES OF THE SYSTEMS TOEPLITZ MATRICES 255
4 Estimation of the Interactor Structure 256
5 A Globally Convergent Adaptive Controller 258
6 Conclusions 259
References 259
APPENDIX 259
CHAPTER 41. DESIGN OF ADAPTIVE DIGITAL SELF-SELECTING MULTIVARIABLE CONTROLLERS 260
Abstract 260
INTRODUCTION 260
DESIGN OF MULTIVARIABLE PI CONTROLLERS 261
DESIGN OF SELF-SELECTING MULTIVARIABLE PI CONTROLLERS 261
DIGITAL SELF-SELECTING CONTROLLER FOR A JET ENGINE 263
CONCLUSION 263
REFERENCES 263
CHAPTER 42. EFFICIENT ALGORITHM FOR ADAPTIVE CONTROL FOR A CLASS OF ÌÉÌÏ PLANT 266
1 Problem Formulation 266
2 Main Results 267
3 Discussion 267
4 Appendix 267
References 269
CHAPTER 43. ADAPTIVE OPTIMIZATION WITH CONSTRAINTS 270
1 Introduction 270
2 Formulation of the problem 270
3 The CAM algorithm 271
4 ODE analysis 272
5 Simulation examples 274
6 Conclusions 274
References 274
CHAPTER 44. FIFTEEN YEARS IN THE LIFE OF AN ADAPTIVE CONTROLLER 276
INTRODUCTION 276
ADAPTIVE CONTROL METHODS 277
KAMYR DIGESTER CHIP LEVEL CONTROL 279
Ti2 CALCINER CONTROL 280
A COMMERCIAL ADAPTIVE CONTROLLER 283
DISCUSSION 283
CONCLUSIONS 284
REFERENCES 284
CHAPTER 45. MERGING OF USER'S KNOWLEDGE INTO IDENTIFICATION PART OF SELF-TUNERS 288
Introduction 288
Theoretical background 288
The problem and its solution 290
Remarks 291
Simulation examples 292
Conclusions 293
References 293
CHAPTER 46. AUTOMATIC INITIALIZATION OF ROBUST ADAPTIVE CONTROLLERS 294
1. Introduction 294
2. The Adaptive Controller 294
3. Relay Feedback 295
4. Finding Design Parameters 297
5. An Initialization Procedure 298
6. Example 298
7. Conclusions 299
8· References 299
CHAPTER 47. AUTOMATIC TUNING OF A DIGITAL CONTROLLER 300
1. Introduction 300
2. Digital Control 300
3. Parameter Estimation 301
4· Control Design 302
5. A Simulation Example 303
6. Applications to HVAC plants 304
7. Conclusions 305
8· References 305
CHAPTER 48. USER SUPPLIED INFORMATION IN THE DESIGN OF LINEAR QUADRATIC GAUSSIAN SELF-TUNING CONTROLLERS 306
INTRODUCTION 306
LQG SELF-TUNER 306
PRELIMINARY DESIGN 307
PROPLEM SOLVED IN THE PAPER 307
METHODOLOGY OF SOLUTION 307
APPLICATION OF METHODOLOGY 308
EXAMPLES OF TRANSLATING 309
PROGRAM ORGANIZATION 310
CONCLUSIONS 311
References 311
CHAPTER 49. ON THE ADAPTIVE CONTROL OF A FLEXIBLE TRANSMISSION SYSTEM 312
1. INTRODUCTION 312
2. THE ADAPTIVE CONTROL APPROACH 312
3. EXPERIMENTAL EVALUATION. 314
4. CONCLUSION. 315
REFERENCES 315
CHAPTER 50. ROBUST ADAPTIVE PREDICTIVE CONTROL OF BIOTECHNOLOGICAL PROCESS: EXPERIMENTAL RESULTS 320
INTRODUCTION 320
PLANT MODEL 320
CONTROL OBJECTIF 320
DERIVATION OF THE CONTROL LAW 321
PARAMETERS ESTIMATION AND ADAPTIVE CONTROL 322
RESULTS 323
CONCLUSION 325
REFERENCES 325
CHAPTER 51. ADAPTIVE CONTROL OF THE TEMPERATURE OF A GLASS FURNACE 326
Abstract 326
1 Introduction 326
2 Description of the Process 326
3 Prediction Model and Control Algorithm 327
4 Industrial Results 330
5 Conclusions 331
References 331
CHAPTER 52. EVALUATION OF A LONG-RANGE ADAPTIVE PREDICTIVE CONTROLLER FOR COMPUTERIZED DRUG DELIVERY SYSTEMS 332
1 Introduction 332
2 Process Control Strategy 333
3 System Description 333
4 Experimental Studies 334
5 Discussions 335
6 Conclusions 336
References 336
CHAPTER 53. PARAMETERS AUTOMATIC DESIGN OF PREDICTIVE CASCADED CONTROLLERS 338
INTRODUCTION 338
FORMULATION OF THE PREDICTIVE CASCADED ALGORITHM (Boucher, 1991a, 1991b) 338
PARAMETERS SELF TUNING 340
APPLICATION TO AN INDUSTRIAL BRUSHLESS MOTOR 341
CONCLUSIONS 343
REFERENCES 343
CHAPTER 54. END POINT ADAPTIVE CONTROL OF A TWO-LINK FLEXIBLE ARM 344
I. INTRODUCTION 344
II. THE EXPERIMENTAL SET-UP 344
III. CONTROL DESIGN 345
IV. EXPERIMENTAL RESULTS 346
CONCLUSIONS 346
REFERENCES 346
CHAPTER 55. CONTINUOUS-TIME ADAPTIVE CONTROL OF CONSUMER ELECTRONIC CIRCUITS 350
Abstract 350
Keywords 350
1. INTRODUCTION 350
2. POWER AMPLIFIER SELECTION 351
3. ADAPTIVE SYSTEMS DESION 352
4. EXPERIMENTAL RESULTS 353
5. CONCLUSIONS 355
6. REFERENCES 355
CHAPTER 56. MODEL REFERENCE ADAPTIVE CONTROL OF A CIRCULATORY MODEL FOR COMBINED NITROPRUSSIDE-DOPAMINE THERAPY1 356
INTRODUCTION 356
DIRECT MRAC DEVELOPMENT 356
SYSTEM DESCRIPTION 357
APPLICATIONAL RESULTS 358
CONCLUSIONS AND RECOMMENDATIONS 360
REFERENCES 360
CHAPTER 57. OPEN LOOP ADAPTIVE FEEDBACK CONTROL OF DEPOSITED ZINC IN HOT-DIP GALVANIZING 362
I. INTRODUCTION 362
II. MODEL OF THE PROCESS 363
Ill. IDENTIFICATION OF THE DISCRETE TIME PLANT MODEL 363
IV. CONTROLLER DESIGN 364
V. OPEN LOOP ADAPTATION 365
VI. IMPLEMENTATION 365
VII. RESULTS 365
VII. CONCLUSIONS 365
REFERENCES 367
CHAPTER 58. NONLINEAR ADAPTIVE CONTROL OF A CONTINUOUS FERMENTATION PROCESS 368
INTRODUCTION 368
PROCESS DESCRIPTION 368
PROCESS MODEL 369
DISCRETIZATION OF NONLINEAR CONTINUOUS SYSTEMS 369
DISCRETE PARAMETER ESTIMATION AND ADAPTIVE CONTROL 370
RESULTS 371
CONCLUSION 372
REFERENCES 372
CHAPTER 59. INTELLIGENT TUNING 374
1. Introduction 374
2. Tuning 374
3· Identification and Control 376
4. Some Performance Limits 377
5· Simple Controllers 379
6. Relay Feedback 381
7. Diagnosis 382
8· Conclusions 383
Acknowledgements 384
References 384
CHAPTER 60. AUTOMATIC TUNING AND ADAPTATION FOR PID CONTROLLERS - A SURVEY 386
1. Introduction 386
2. Adaptive Techniques 386
3. Modeling 387
4. Control Design 388
5· Overview of industrial products 390
6. Conclusions 391
7. References 391
CHAPTER 61. DOMINANT POLE DESIGN - A UNIFIED VIEW OF PID CONTROLLER TUNING 392
1. Introduction 392
2. Controller and Specifications 392
3· Controller Design 393
4. Examples 394
5· Relations to other methods 395
6. Conclusions 395
7. References 395
8· Figures 396
CHAPTER 62. THE NORMAL-MODE-INACTION ADAPTIVE PID CONTROLLER 398
Abstract 398
1 Introduction 398
2 Initialization Of The Adaptive Controller 398
3 The NMI Adaptive PID Controller 399
4 Supervision of the NMI Adaptive PID Controller 400
5 The performance of the NMI Adaptive PID Controller 400
6 Conclusoins 401
References 402
CHAPTER 63. USE OF INTELLIGENT TUNING IN A HIERARCHICAL CONTROL SYSTEM FOR AUTOMATED FISH PROCESSING 404
INTRODUCTION 404
WORKCELL DEVELOPMENT 404
THEORETICAL CONSIDERATIONS 405
INTELLIGENT TUNING 408
ACKNOWLEDGMENT 408
REFERENCES 408
CHAPTER 64. MULTIVARIABLE CONTROL TUNING WITH AN EXPERT SYSTEM 410
INTRODUCTION 410
DESIGN SESSION 410
CONTROL OBJECTIVES 411
CONTROL DESIGN 412
CONCLUSIONS 415
REFERENCES 415
CHAPTER 65. A POSITION CONTROL AUTOTUNER FOR HANDLING SYSTEMS 416
1. INTRODUCTION 416
2. THE AUTOTUNING APPROACH 416
3. EXPERIMENTAL EVALUATION 418
4. CONCLUSION 419
REFERENCES 419
CHAPTER 66. THE "SYMMETRISCHE OPTIMUM" AND THE AUTO-CALIBRATION OF PID CONTROLLERS 422
I. INTRODUCTION 422
II. THE KESSLER'S "SYMMETRISCHE OPTIMUM" 422
III. AUTO-CALIBRATION OF PICONTROLLERS 423
IV. AUTO-CALIBRATION OF PID CONTROLLER 424
V. COMPARISON WITH ZIEGLER-NICHOLS TUNING RULES 425
VI. SIMULATIONS AND EXPERIMENTAL RESULTS 426
VII. CONCLUSIONS 426
REFERENCES 427
CHAPTER 67. HARDWARE IMPLEMENTATION AND EVALUATION OF A KNOWLEDGE-BASED TUNER FOR A SERVO MOTOR 428
INTRODUCTION 428
SYSTEM DEVELOPMENT 429
THE EXPERIMENTAL SYSTEM 429
MODEL OF THE PHYSICAL SYSTEM 430
KNOWLEDGE BASE 430
RESULTS 431
REFERENCES 432
CHAPTER 68. KNOWLEDGE BASED ADAPTIVE CONTROL WITH LEARNING AND INTELLIGENT ABILITIES 434
1 INTRODUCTION 434
2 ADAPTIVE CONTROL WITH INTELLIGENT ABILITIES 435
3 ADAPTIVE CONTROL OF NONLINEAR PROCESSES 437
4 KNOWLEDGE BASE DADAPTIVE CONTROLLER 438
5 CONCLUSIONS 439
REFERENCES 439
CHAPTER 69. ACTIVE NOISE CANCELLATION IN DISTRIBUTED SYSTEMS USING ADAPTIVE CONTROL 440
PROBLEM STATEMENT 440
DISTRIBUTED IMPLEMENTATION 442
A SIMULATION EXAMPLE 443
PERFORMANCE OF THE ADAPTIVE CONTROL ALGORITHM 443
Acknowledgements 444
CHAPTER 70. ADAPTIVE SIGNAL PROCESSING APPLIED IN TELECOMMUNICATIONS 446
ABSTRACT 446
1. Introduction 446
2. Macro Trend 446
Acknowledgments 456
REFERENCES 456
CHAPTER 71. APPLICATION OF BLIND EQUALIZATION TECHNIQUES TO VOICEBAND AND RF MODEMS 458
INTRODUCTION 458
THE EQUALIZATION PROBLEM IN BROADCAST COMMUNICATIONS 459
BLIND EQUALIZATION 461
DEALING WITH NARROWBAND INTERFERENCE 462
A CURRENT PROBLEM: MISCONVERGENCE DUE TO INCOMPLETE INPUT EXCITATION 462
CONCLUSIONS 466
ACKNOWLEDGMENTS 466
REFERENCES 466
CHAPTER 72. WELL-CONDITIONED RECURSIVE LEAST-SQUARED ESTIMATION ALGORITHMS 468
1. Introduction: Signal Estimation using Linear Regression 468
2. RLS Estimation Algorithms using Taylor Expansions 469
3. RLS Estimation Algorithms using Orthogonal Expansions 471
4. Conclusions: Unsolved Research Problems 472
References 473
CHAPTER 73. A MODULAR ARCHITECTURE FOR THE ADAPTIVE NORMALIZED SLIDING WINDOW COVARIANCE LATTICE FILTER 474
I. INTRODUCTION 474
II. THE GEOMETRIC APPROACH 474
III. THE MODULAR DECOMPOSITION OF THE BASIC RLS LATTICE ALGORITHMS 476
IV. THE ANSWC ALGORITHM 478
CONCLUSION 479
REFERENCES 479
CHAPTER 74. A NEW FTF9N STABILIZED RECURSIVE ALGORITHM, IMPLEMENTATION ON FINITE-PRECISION 480
INTRODUCTION 480
THE RLS ALGORITHM 481
THE FTF ALGORITHM 481
THE FTF9N STABILIZED ALGORITHM 482
IMPLEMENTATION OF FTF9N STABILIZED ALGORITHM IN FINITE PRECISION ARITHMETIC 483
SIMULATIONS RESULT 484
CONCLUSION 484
REFERENCES 484
CHAPTER 75. CONSISTENCY AND MINIMALITY FOR THE PREWINDOWED PREDICTION PROBLEM 486
I Introduction 486
II Background 486
Ill Consistency in Fast Algorithms 487
IV Some Open Questions 490
References 491
CHAPTER 76. IMAGE RESTORATION USING EXTENDED KALMAN FILTERS1 492
INTRODUCTION 492
IMAGE MODELS 492
BLUR MODELS 492
RESTORATION USING THE EXTENDED KALMAN FILTER 493
RESULTS 494
CONCLUSIONS AND RECOMMENDATIONS 494
REFERENCES 495
CHAPTER 77. A MULTISCALE TIME-VARYING APPROACH TO MOVING SOURCE TRACKING 496
Abstract 496
1 Introduction 496
2 A spatio-temporal model of the data 496
3 Estimation of the time-Varying AR model 498
4 Simulation results 500
5 Conclusion 500
References 500
CHAPTER 78. MAXIMUM LIKELIHOOD LOCATION ESTIMATION OF WIDEBAND SOURCES USING THE EM ALGORITHM 502
Introduction 502
Data Model 502
EM-Algorithm 504
Approximate MLE 504
Approximate Dual MLE 505
Concluding Remarks 506
References 506
CHAPTER 79. LMS AND FRLS 2-D LATTICE FILTERS 508
INTRODUCTION 508
THE 2-D AR MODELING PROBLEM 509
THE 2-D LATTICE STRUCTURE FOR AR MODELING 509
THE 2-D ADAPTIVE LATTICE LEAST MEAN SQUARES ALGORITHM (TDAL-LMS) 510
NORMALIZED 2-D ADAPTIVE LATTICE LMS ALGORITHM (TDAL-NLMS) 510
2-D ADAPTIVE LATTICE FAST RECURSIVE LEAST SQUARES ALGORITHM (TDAL-FRLS) 510
SIMULATION RESULTS 511
THE 2-D JOINT PROCESS LATTICE ESTIMATOR 511
RESTORATION OF NOISY IMAGES 512
CONCLUSION 512
REFERENCES 512
CHAPTER 80. ADAPtlVE PROCESSING OF MULTIDIMENSIONAL SIGNALS: FROM PRINCIPLES TO SIMULATION 514
Abstract 514
I- INTRODUCTION 514
II- LMS MULTIDIMENSIONAL FILTERING 514
III- THE ADFMD SOFTWARE FOR PC SIMULATION 515
IV- FLS MULTIDIMENSIONAL FILTERING 515
V- MODULAR STRUCTURES:THE QR APPROACH 516
VI- CONCLUSION 517
References 518
CHAPTER 81. ADAPTIVE EQUALIZATION OF DIGITAL LINE-OF-SIGHT RADIO SYSTEMS 520
INTRODUCTION 520
DECISION-FEEDBACK EQUALIZERS 520
FRACTIONALLY-SPACED EQUALIZERS 521
ADAPTATION ALGORITHMS 522
BLIND ADAPTATION 523
FURTHER ISSUES 524
CONCLUSIONS 525
REFERENCES 525
CHAPTER 82. A MODIFIED BAYESIAN ALGORITHM WITH DECISION FEEDBACK FOR BLIND ADAPTIVE EQUALIZATION 526
1 Introduction 526
2 MAP Estimation Algorithm 527
3 Bayesian/DF Algorithm 528
4 Computer Simulations 528
5 Conclusion 529
References 529
CHAPTER 83. THE NON STATIONARITY DEGREE: CAN AN ADAPTIVE FILTER BE WORSE THAN NO PROCESSING? 532
I. INTRODUCTION 532
II. NON STATIONARY ADAPTIVE FILTERING 532
III. RANDOM WALK FILTER 533
IV. THE MARKOVIAN FILTER 534
V. TRACKING PERFORMANCE : A GENERAL METHODOLOGY 535
VI. CONCLUSION: JUMPS 537
REFERENCES 537
CHAPTER 84. ADAPTIVE CHANNEL ESTIMATION FOR MAXIMUM LIKELIHOOD SEQUENCE ESTIMATION 538
INTRODUCTION 538
CHANNEL MODEL AND ML SEQUENCE ESTIMATION 538
THE VITERBI ALGORITHM 539
ML RECEIVER BASED ON VITERBI ALGORITHM AND ADAPTIVE CHANNEL ESTIMATOR 539
MODIFICATIONS OF THE VITERBI RECEIVER 541
JOINT BLIND CHANNEL AND DATA SEQUENCE ESTIMATION 542
CONCLUSIONS 543
REFERENCES 543
CHAPTER 85. ROBUST ADAPTIVE QUANTIZATION VIA KALMAN FILTERING TECHNIQUES1 544
1 Introduction 544
2 Kaiman Filter Based Adaptive Quantization 545
3 Enhanced Dequantizer Based on Kalman Filtering 546
4 Application of Kaiman Smoothing to the Dequantizer 547
5 Simulations 548
6 Conclusions 549
References 549
AUTHOR INDEX 550
KEYWORD INDEX 552