E-Book, Englisch, 557 Seiten, Web PDF
Reihe: IFAC Workshop Series
Proceedings of the 2nd IFAC Workshop, Lund, Sweden, 1-3 July 1986
E-Book, Englisch, 557 Seiten, Web PDF
Reihe: IFAC Workshop Series
ISBN: 978-1-4832-9808-5
Verlag: Elsevier Science & Techn.
Format: PDF
Kopierschutz: 1 - PDF Watermark
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Weitere Infos & Material
1;Front Cover;1
2;Adaptive Systems in Control and Signal Processing 1986: Proceedings of the 2nd IFAC Workshop Lund, Sweden, 1—3 July 1986
;4
3;Copyright Page;5
4;Table of Contents
;10
5;PREFACE;8
6;Table of Contents;10
7;Part 1: PLENARY PAPERS;14
7.1;Chapter 1. ADAPTIVE INVERSE CONTROL;14
7.1.1;INTRODUCTION;14
7.1.2;ADAPTIVE FILTERS;14
7.1.3;DIRECT PLANT IDENTIFICATION;15
7.1.4;INVERSE PLANT IDENTIFICATION;15
7.1.5;ADAPTIVE CONTROL OF PLANT DYNAMICS;16
7.1.6;ADAPTIVE PLANT-NOISE CANCELLING;16
7.1.7;ADAPTIVE INVERSE CONTROL;17
7.1.8;CONCLUSION;17
7.1.9;REFERENCES;17
7.2;Chapter 2. DETECTION OF CHANGES IN SIGNALS ANDSYSTEMS;20
7.2.1;PROBLEMS STATEMENT AND APPLICATIONEXAMPLES;20
7.2.2;GENERATION OF THE SIGNALS TO BEMONITORED;21
7.2.3;DESIGN OF DECISION RULES;22
7.2.4;CONCLUSION;24
7.2.5;REFERENCES;24
7.3;Chapater 3. ALGORITHMS FOR LQG SELF-TUNINGCONTROL BASED ON INPUT-OUTPUT DELTAMODELS;26
7.3.1;INTRODUCTION;26
7.3.2;ALGORITHMIC TOOLS;27
7.3.3;STATE ESTIMATION AND OUTPUT PREDICTION;27
7.3.4;JOINT PARAMETER AND STATE ESTIMATION;29
7.3.5;REFERENCES;31
7.3.6;APPENDIX - PASCAL PROCEDURES;31
7.4;Chapter 4. CONTINUOUS-TIME SELF-TUNING CONTROL— A UNIFIED APPROACH;32
7.4.1;1. INTRODUCTION;32
7.4.2;2. SMITH'S PREDICTOR;32
7.4.3;3. EMULATORS;33
7.4.4;4. SOME SPECIAL CASES.;34
7.4.5;5. ADAPTIVE EMULATORS;35
7.4.6;6. CONCLUSION;36
7.4.7;References;36
7.5;Chapter 5. A CLASS OF ROBUST ADAPTIVE CONTROLALGORITHMS;38
7.5.1;INTRODUCTION;38
7.5.2;THE PLANT MODEL;39
7.5.3;CONTROL SYSTEM DESIGN;39
7.5.4;ROBUST PARAMETER ESTIMATION;39
7.5.5;THE ROBUST ADAPTIVE CONTROLLER;40
7.5.6;WEAKLY COUPLED MULTIVARIABLE SYSTEMS;41
7.5.7;TIME DELAY SYSTEMS;42
7.5.8;CONCLUSIONS;42
7.5.9;REFERENCES;42
7.6;Chapter 6. AN ADAPTIVE CONTROLLER BASED UPONCONTINUOUS ESTIMATION OF THE CLOSEDLOOP FREQUENCY RESPONSE;44
7.6.1;1. INTRODUCTION;44
7.6.2;2. BASIC PRINCIPLES OF THE NEW ADAPTIVECONTROLLER;44
7.6.3;3. THE ESTIMATOR;45
7.6.4;4. ADAPTATION OF THE CONTROLLER;46
7.6.5;5. VERIFICATION OF THE THEORY BY EXPERIMENTS;47
7.6.6;6. CONCLUSION;47
7.6.7;7. ACKNOWLEDGEMENTS;48
7.6.8;8. REFERENCES;48
7.7;Chapter 7. A COMPARISON BETWEEN ROBUST ANDADAPTIVE CONTROL OF UNCERTAINSYSTEMS;56
7.7.1;1. INTRODUCTION;56
7.7.2;2. FUNDAMENTAL ISSUES;56
7.7.3;3. APPROACHES TO ROBUST DESIGN;57
7.7.4;4. ADAPTIVE CONTROL;57
7.7.5;5. EXAMPLES;58
7.7.6;6. ROBUST AND ADAPTIVE CONTROL;61
7.7.7;7. REFERENCES;61
7.8;Chapter 8. A ROBUST POLE PLACEMENT ALGORITHMFOR ADAPTIVE CONTROL;62
7.8.1;INTRODUCTION;62
7.8.2;DESCRIPTION OF PROBLEM;62
7.8.3;METHOD;63
7.8.4;APPLICATION TO THE DIOPHANTINE EQUATION;63
7.8.5;REFERENCES;65
7.9;Chapter 9. AN ALGORITHM FOR ADAPTATION OF AROBUST CONTROLLER TO REDUCED PLANTUNCERTAINTY;68
7.9.1;1. INTRODUCTION;68
7.9.2;2. STATEMENT OF THE PROBLEM;68
7.9.3;3. THE FORM OF THE FULL UNCERTAINTY SOLUTION.;69
7.9.4;4. LOW FREQUENCY ADAPTATION;70
7.9.5;5. HIGH FREQUENCY ADAPTATION;70
7.9.6;6 PREFILTER DESIGN;71
7.9.7;7. A DESIGN EXAMPLE;71
7.9.8;8. CONCLUSIONS;71
7.9.9;REFERENCES;73
7.10;Chapter 10. ROBUST DESIGN OF ADAPTIVE CONTROLSYSTEMS USING CONIC SECTOR THEORY;74
7.10.1;INTRODUCTION;74
7.10.2;ROBUST STABILITY RESULTS;74
7.10.3;ILLUSTRATIVE EXAMPLE;76
7.10.4;CONCLUSIONS;78
7.10.5;REFERENCES;78
7.11;Chapter 11. ADAPTIVE GENERALIZED PREDICTIVECONTROL WITH MULTIPLE REFERENCEMODEL;80
7.11.1;INTRODUCTION;80
7.11.2;MONO INPUT MONO OUTPUT SYSTEMS;81
7.11.3;ONE INPUT MOLTI OUTPUT SYSTEMS;83
7.11.4;MULTI INPUT MULTI OUTPUT SYSTEMS;84
7.11.5;NUMERICAL AND EXPERIMENTAL RESULTS;84
7.11.6;REFERENCES;85
7.12;Chapter 12. EXTENDED IMPLICIT MODELS ANDAPPLICATION TO LQ ADAPTIVEOPTIMIZATION;86
7.12.1;INTRODUCTION;86
7.12.2;A BRIEF SUMMARY OF PREVIOUS IMPLICITMODELLING THEORY;86
7.12.3;EXTENDED IMPLICIT MODELS;87
7.12.4;LQ OPTIMIZATION IN PRESENCE OF DITHERNOISE;88
7.12.5;M-STEP ADAPTIVE LQ OPTIMIZATION BASEDON THE IDENTIFICATION OF EXTENDED IMPLICITMODELS;89
7.12.6;VARIATIONAL ADAPTIVE CONTROL SCHEME;90
7.12.7;CONCLUSIONS;92
7.12.8;REFERENCES;92
7.13;Chapter 13. SINGLE PREDICTOR VS. MULTI PREDICTORBASED LONG-RANGE SELF-TUNINGADAPTIVE CONTROL;94
7.13.1;INTRODUCTION;94
7.13.2;LQ ADAPTIVE CONTROL BYMULTIPLE PREDICTORS;94
7.13.3;COMPARISON WITH A SINGLE-PREDICTORBASED SELF-TUNING REGULATOR;97
7.13.4;CONCLUSIONS AND OPEN PROBLEMS;97
7.13.5;REFERENCES;97
7.13.6;APPENDIX;98
7.14;Chapter 14. POLYNOMIAL LQ CONTROL SYNTHESIS FORDELTA-OPERATOR MODELS;100
7.14.1;1. INTRODUCTION;100
7.14.2;2. LQ OPTIMAL CONTROL PROBLEM;100
7.14.3;3. OPERATORS USED FOR A PLANT DESCRIPTION;101
7.14.4;4. ALGORITHMS OF THE SYNTHESIS;102
7.14.5;5. EXAMPLE;103
7.14.6;6. CONCLUSION;104
7.14.7;REFERENCES;104
7.15;Chapter 15. HYBRID ADAPTIVE REGULATION FORCONTINUOUS TIME SYSTEMS;106
7.15.1;1. Introduction;106
7.15.2;2. Hybrid Adaptive Regulator (HAR);106
7.15.3;3. Stability Result;107
7.15.4;4. Conclusions;110
7.15.5;5. References;110
7.16;Chapter 16. ON PARALLEL FEEDFORWARD ANDSIMPLIFIED ADAPTIVE CONTROL;112
7.16.1;INTRODUCTION;112
7.16.2;THE SIMPLIFIED ADAPTIVE CONTROL PROBLEM;112
7.16.3;EXAMPLES;115
7.16.4;REFERENCES;116
7.17;Chapter 17. ADAPTIVE CONTROL BASED ONORTHONORMAL SERIES REPRESENTATION;118
7.17.1;1. INTRODUCTION;118
7.17.2;2. MODELLING AND CONTROL USING A LAGUERRENETWORK;118
7.17.3;3. A DETERMINISTIC EXPLICIT SELF-TUNER;121
7.17.4;4. PRACTICAL ASPECTS AND IMPLEMENTATION;122
7.17.5;5. CONCLUSIONS;122
7.17.6;6. REFERENCES;122
7.18;Chapter 18. SELF-TUNING CONTROL OF PARABOLICDISTRIBUTED PARAMETER SYSTEMS;128
7.18.1;INTRODUCTION;128
7.18.2;PROBLEM DESCRIPTION;128
7.18.3;MODEL DISCRETIZATION;128
7.18.4;MULTIVARIABLE SELF-TUNING CONTROLLER;129
7.18.5;TWOSELF PROGRAM;129
7.18.6;TEMPERATURE CONTROL OF A PLASTICSEXTRUDER;129
7.18.7;SIMULATION RESULTS;130
7.18.8;CONCLUSIONS;130
7.18.9;REFERENCES;130
7.19;Chapter 19. A SELF-TUNING CONTROLLER FOR MIMONONLINEAR SYSTEMS;132
7.19.1;ABSTRACT;132
7.19.2;1. INTRODUCTION;132
7.19.3;2. SYSTEM DESCRIPTION;132
7.19.4;3. A NEW SELF-TUNING CONTROLLER;133
7.19.5;4. SIMULATION RESULTS;135
7.19.6;5. CONCLUSIONS;136
7.19.7;ACKNOWLEDGMENTS;136
7.19.8;REFERENCES;136
7.20;Chapter 20. DISTURBANCE DECOUPLING ADAPTIVECONTROL;138
7.20.1;1. INTRODUCTION: IF FEEDFORWARD IS SO GOOD, WHY IS ITNOT USED MORE FREQUENTLY?;138
7.20.2;2. ALTERNATIVES FOR ADAPTIVE CONTROL;139
7.20.3;3. SIMULATIONS;141
7.20.4;4. CONCLUSIONS;143
7.20.5;REFERENCES;143
7.21;Chapter 21. DISCRETE-TIME ADAPTIVE CONTROL FORPERIODICALLY TIME-VARYING SYSTEMS;144
7.21.1;INTRODUCTION;144
7.21.2;PROBLEM STATEMENT;144
7.21.3;ADAPTIVE CONTROL ALGORITHM;145
7.21.4;CONVERGENCE ANALYSIS;146
7.21.5;CONCLUSION;148
7.21.6;REFERENCES;148
7.22;Chapter 22. FIXED-POINT THEOREMS FOR STABILITYANALYSIS OF ADAPTIVE SYSTEMS;150
7.22.1;1. INTRODUCTION;150
7.22.2;2. THE TUNED SYSTEM AND LINEARIZATION;150
7.22.3;3. THE LINEARIZED RESPONSE;152
7.22.4;4. TRANSIENT ANALYSIS;153
7.22.5;CONCLUSIONS;154
7.22.6;REFERENCES;154
7.23;Chapter 23. ROBUST ADAPTIVE CONTROL USINGREDUCED ORDER MODELS;156
7.23.1;INTRODUCTION;156
7.23.2;ROBUST ADAPTIVE CONTROL IN THE PRESENCE OFBOUNDED DISTURBANCES;156
7.23.3;ROBUST ADAPTIVE CONTROL USING REDUCEDORDER MODELS;158
7.23.4;REFERENCES;160
7.24;Chapter 24. ON THE ASYMPTOTIC BEHAVIOUR OF ANADAPTIVE POLE-PLACEMENT ALGORITHM;162
7.24.1;INTRODUCTION;162
7.24.2;PROBLEM FORMULATION;162
7.24.3;GLOBAL STABILITY;163
7.24.4;CONSISTENCY OF THE REGULATOR PARAMETERESTIMATES;164
7.24.5;PERSISTENCE OF EXCITATION;166
7.24.6;CONCLUSION;167
7.24.7;REFERENCES;167
7.25;Chapter 25. STABILITY BOUNDS FOR SLOWADAPTATION: AN INTEGRAL MANIFOLDAPPROACH;168
7.25.1;INTRODUCTION;168
7.25.2;1. A REDUCED ORDER PARAMETRIZATION;168
7.25.3;2. UPDATE LAW;169
7.25.4;3. INTEGRAL MANIFOLD FOR DISCRETESLOW ADAPTATION;170
7.25.5;4. STABILITY IN THE SLOW MANIFOLD;171
7.25.6;5. AN INSTABILITY RESULT;172
7.25.7;6. DISCUSSION;172
7.25.8;ACKNOWLEDGEMENTS;173
7.25.9;REFERENCES;173
7.26;Chapter 26. REVISITING THE MIT RULE FOR ADAPTIVECONTROL;174
7.26.1;ABSTRACT;174
7.26.2;1 . INTRODUCTION;174
7.26.3;2. THE MIT RULE;174
7.26.4;3. INSTABILITY MECHANISMS;175
7.26.5;4. STABILITY ANALYSIS VIA AVERAGING:RESCUING THE MIT RULE;176
7.26.6;5. CONSEQUENCES AND CONCLUSIONS;177
7.26.7;ACKNOWLEDGEMENTS;178
7.26.8;REFERENCES;178
7.27;Chapter 27. DESIGN OF ADAPTIVE ALGORITHMS FORTHE TRACKING OF TIME VARYING SYSTEMS;180
7.27.1;1 .INTRODUCTION;180
7.27.2;TWO TYPICAL EXAMPLES;180
7.27.3;THEORETICAL PEREQUISITES;181
7.27.4;2.MONOSTEP ADAPTIVE ALGORITHMS;182
7.27.5;MAIN THEOREMS;183
7.27.6;APPLICATIONS;185
7.27.7;MULTISTEP ADAPTIVE ALGORITHMS;186
7.27.8;CONCLUSION;186
7.27.9;REFERENCES;186
7.28;Chapter 28. STABLE ADAPTIVE OBSERVERS FORNONLINEAR TIME-VARYING SYSTEMS;188
7.28.1;ABSTRACT;188
7.28.2;1. INTRODUCTION;188
7.28.3;2. TRANSFORMATION TO A CANONICAL REPRESENTATION;189
7.28.4;3. THE ADAPTIVE OBSERVER;189
7.28.5;4. STABILITY CONDITIONS FOR THE ADAPTIVE OBSERVER;190
7.28.6;5. APPLICATION TO BILINEAR SYSTEMS;191
7.28.7;6. APPLICATION TO A NONLINEAR BIQTECHNQLOGICALSYSTEM;192
7.28.8;7. CONCLUSIONS;192
7.28.9;ACKNOWLEDGEMENTS;193
7.28.10;REFERENCES;193
7.29;Chapter 29. PARAMETER TRACKING OF TIME-VARYINGLINEAR SYSTEMS WITH NON-GAUSSIANDRIVING NOISE;194
7.29.1;INTRODUCTION;194
7.29.2;THE NOISE MODEL;194
7.29.3;TIME-VARYING SYSTEMS;196
7.29.4;ABOUT THE PROOF;197
7.29.5;CONCLUSIONS;197
7.29.6;REFERENCES;197
7.30;Chapter 30. TRACKING OF NONSTATIONARY SYSTEMSBY MEANS OF DIFFERENT PREDICTIONERROR DIRECTION FORGETTINGTECHNIQUES;198
7.30.1;1.INTRODUCTION;198
7.30.2;2.RECURSIVE LEAST-SQUARESWITH FORGETTING FACTORS;199
7.30.3;3.SIMULATION RESULTS;200
7.30.4;ACKNOWLEDGEMENTS;203
7.30.5;REFERENCES;203
7.31;Chapter 31. DIRECTIONAL TRACKING OF REGRESSIONTYPEMODEL PARAMETERS;204
7.31.1;INTRODUCTION;204
7.31.2;REGRESSION-TYPE MODELS;204
7.31.3;BAYESIAN ESTIMATION;205
7.31.4;RESTRICTED EXPONENTIAL FORGETTING;205
7.31.5;NOVEL ALGORITHM OFPARAMETER TRACKING;206
7.31.6;SPECIAL ALGORITHMS;207
7.31.7;ILLUSTRATIVE EXAMPLE;208
7.31.8;CONCLUDING REMARKS;209
7.31.9;REFERENCES;209
7.32;Chapter 32. REQUIREMENTS OF ADAPTIVE TECHNIQUESFOR ENHANCED CONTROL OF LARGEDIESEL ENGINES;210
7.32.1;1. INTRODUCTION;210
7.32.2;2. NONLINEAR AND LINEARIZED DYNAMICS;210
7.32.3;3. CONTROL PROPERTIES;212
7.32.4;4. COMPLEX SYSTEMS;213
7.32.5;5. ADAPTIVE TECHNIQUES AND SIGNALPROCESSING;214
7.32.6;6. CONCLUSION;215
7.32.7;7. ACKNOWLEDGEMENTS;215
7.32.8;8. REFERENCES;215
7.33;Chapter 33. SELF-TUNING REGULATORS USED FOR SHIPCOURSE KEEPING;216
7.33.1;1. INTRODUCTION;216
7.33.2;2. MATHEMATICAL MODELS;217
7.33.3;3. KAIMAN FILTER;217
7.33.4;4. CONTROL ALGORITHMS;218
7.33.5;5. SIMULATIONS;218
7.33.6;6. SEA EXPERIMENTS;220
7.33.7;7. CONCLUSION;221
7.33.8;REFERENCES;221
7.34;Chapter 34. LINEAR QUADRATIC SELF-TUNINGREGULATORS IN PAPER-MACHINECONTROL SYSTEMS;222
7.34.1;INTRODUCTION;222
7.34.2;CONTROLLED PROCESS;222
7.34.3;CONTROL STRUCTURE;222
7.34.4;ADAPTIVE REGULATOR;223
7.34.5;SOFTWARE ENVIRONMENT;223
7.34.6;PRACTICAL IMPLEMENTATION;224
7.34.7;PRACTICAL RESULTS ANDFUTURE DEVELOPMENT;224
7.34.8;REFERENCES;224
7.35;Chapter 35. APPLICATION OF ADAPTIVE PREDICTIVECONTROL FOR THE BOTTOMTEMPERATURE OF A GLASS FURNACE;226
7.35.1;1. INTRODUCTION;226
7.35.2;2. DESCRIPTION OF THE PROCESS AND OF THEHIERARCHICAL CONTROL STRUCTURE;226
7.35.3;3. CONTROL ALGORITHM;227
7.35.4;4. REAL TIME OPERATION RESULTS;229
7.35.5;CONCLUSION;229
7.35.6;REFERENCES;229
7.36;Chapter 36. ON THE APPLICABILITY OF ADAPTIVECONTROL;232
7.36.1;1. INTRODUCTION;232
7.36.2;2. PROBLEM FORMULATION;233
7.36.3;3. THE ADAPTIVE CONTROL APPLICABILITY;235
7.36.4;CONCLUSIONS;237
7.36.5;REFERENCES;238
7.37;Chapter 37. AN ADAPTIVE CONTROLLER FOR SKODATWENTY-ROLLS COLD ROLLING MILLS;240
7.37.1;INTRODUCTION;240
7.37.2;THE ROLLING MILL;240
7.37.3;CONTROLLER DESIGN;241
7.37.4;MATHEMATICAL MODEL;241
7.37.5;HARDWARE AND SOFTWARE;241
7.37.6;EXPERIENCE;242
7.37.7;CONCLUSIONS;242
7.37.8;REFERENCES;242
7.38;Chapter 38. ADAPTIVE MINIMUM ENERGY CONTROL OFLARGE SHIP DIESEL ENGINES;244
7.38.1;1. INTRODUCTION;244
7.38.2;2. ENGINE DESCRIPTION;244
7.38.3;3. STEADY STATE ENGINE MODELLING;245
7.38.4;4. DYNAMIC ENGINE MODELLING;246
7.38.5;5. ADAPTIVE REGULATOR STRATEGY;246
7.38.6;6. CONCLUSIONS;249
7.38.7;7. ACKNOWLEDGEMENTS;249
7.38.8;8. REFERENCES;249
7.39;Chapter 39. ADAPTIVE CONTROL OF MISSILE ATTITUDE;250
7.39.1;INTRODUCTION;250
7.39.2;FIXED GAIN CONTROL SYSTEM MODEL;250
7.39.3;ADAPTIVE PROPOSAL;252
7.39.4;RESULTS;253
7.39.5;CONSENTS AND CONCLUSIONS;254
7.39.6;REFERENCES;255
7.40;Chapter 40. A MICROPROCESSOR IMPLEMENTATION OFA SELF-TUNING CONTROLLER;256
7.40.1;INTRODUCTION;256
7.40.2;SELF-TUNING ALGORITHM;256
7.40.3;IMPLEMENTATION;257
7.40.4;EXPERIMENTAL RESULTS;258
7.40.5;DISCUSSION AND CONCLUSIONS;260
7.40.6;ACKNOWLEDGMENT;260
7.40.7;REFERENCES;260
7.41;Chapter 41. IMPLEMENTATION OF FEEDBACK/FEEDFORWARD ADAPTIVE CONTROLLERSIN CHEMICAL PROCESSES;262
7.41.1;INTRODUCTION;262
7.41.2;THE ALGORITHM;262
7.41.3;RESULTS AND DISCUSSION;263
7.41.4;CONCLUSION;264
7.41.5;REFERENCES;264
7.42;Chapter 42. NON-DIMENSIONAL REDUCED PARAMETERSELF-TUNING CONTROL OF HEATEXCHANGERS BY USING IDENTIFIEDDYNAMICS FROM STEADY-STATE DATA;266
7.42.1;1. INTRODUCTION;266
7.42.2;2. BASIC EQUATIONS AND NOMENCLATURE;266
7.42.3;3. PI CONTROL LAW WHICH ASSIGNSFIXED DAMPING RATIO;267
7.42.4;4. DETERMINATION 0F;268
7.42.5;5. PROCEDURE OF SELF-TUNING CONTROL;269
7.42.6;6. EXPERIMENTAL RESULTS;270
7.42.7;7. CONCLUSIONS;271
7.42.8;REFERENCES;271
7.43;Chapter 43. ON ADAPTIVE CONTROL OF THERMALPROCESSES BY A PREDICTIVE3-LEVEL-CONTROLLER;272
7.43.1;1. INTRODUCTION;272
7.43.2;2. CONCEPT OF ADAPTIVE PREDICTIVE SWITCHINGCONTROL;272
7.43.3;3. IDENTIFICATION OF THE THERMAL PROCESS;273
7.43.4;4. PREDICTIVE CONTROL STRATEGY;274
7.43.5;5. EVALUATION OF THE PREDICTED OUTPUT SEQUENCES;275
7.43.6;6. RESULTS FORM DIGITAL SIMULATIONS;275
7.43.7;7. CONCLUSIONS;275
7.43.8;8. REFERENCES;275
7.44;Chapter 44. EXPERIMENTAL STUDY ON DISCRETE TIMEADAPTIVE CONTROL OF AN INDUSTRIALROBOT ARM;278
7.44.1;INTRODUCTION;278
7.44.2;EXPERIMENTAL APPARATUS;278
7.44.3;ROBOT ARM CONTINUOUS TIME MODEL;279
7.44.4;DISCRETE TIME CONTROLLER DESIGN;279
7.44.5;RESULTS AND DISCUSSION;281
7.44.6;CONCLUSIONS AND FURTHER WORK;281
7.44.7;REFERENCES;282
7.45;Chapter 45. ADAPTIVE CONTROL OF A FLEXIBLE ARM;284
7.45.1;I- INTRODUCTION;284
7.45.2;II- DESCRIPTION OP THE EXPERIMENTAL FLEXIBLEARM;284
7.45.3;Ill- PROCESS MODELLING;284
7.45.4;IV- IDENTIFICATION;285
7.45.5;V- CONTROL;285
7.45.6;VI- CONCLUSIONS;286
7.45.7;VII- REFERENCEES;286
7.46;Chapter 46. ADAPTIVE CONTROL OF A FLEXIBLESTRUCTURE;290
7.46.1;INTRODUCTION;290
7.46.2;THE FOUR-DISK SYSTEM;290
7.46.3;DISTURBANCES;291
7.46.4;IDENTIFICATION GOALS/ASSUMPTIONS;291
7.46.5;MEASUREMENT NOISE ANDLEAST-SQUARES IDENTIFICATION;292
7.46.6;MODIFIED FILTERED LEAST-SQUARES (MFLS);292
7.46.7;FREQUENCY-CONSTRAINT PREFILTERING;293
7.46.8;ASSUMED-DAMPING IDENTIFICATIONFOR ADAPTIVE SERVOS (ADIDAS);293
7.46.9;ADAPTIVE CONTROL GOALS;294
7.46.10;RADIAL POLE-PROJECTION (RPP);294
7.46.11;BUMPLESS CONTROL STRUCTURE;294
7.46.12;PERFORMANCE COMPARISON:ADAPTIVE VERSUS ROBUST;295
7.46.13;CONCLUSION;295
7.46.14;REFERENCES;295
7.47;Chapter 47. AN APPLICATION OF ADAPTIVEFEEDFORWARD CONTROL TO ROBOTICS;296
7.47.1;1 Introduction;296
7.47.2;2 The Trajectory Learning Algorithm;296
7.47.3;3 An Implementation Of The Algorithm;298
7.47.4;4 Convergence;298
7.47.5;5 Conclusions;300
7.47.6;Acknowledgments;301
7.47.7;References;301
7.48;Chapter 48. MULTIVARIABLE SELF-TUNING FORROBOTIC SERVO APPLICATIONS;302
7.48.1;1. INTRODUCTION;302
7.48.2;2. DESIGN PHILOSOPHY;302
7.48.3;3. IMPLEMENTATION ISSUES;304
7.48.4;4. APPLICATION;305
7.48.5;5. CONCLUSION;306
7.48.6;6. ACKNOWLEDGMENTS;306
7.48.7;7. REFERENCES;306
7.49;Chapter 49. CHANGE DETECTION AND DIAGNOSIS FORVIBRATION MONITORING;310
7.49.1;INTRODUCTION;310
7.49.2;GLOBAL CHANGE DETECTION;310
7.49.3;APPLICATION TO THE VIBRATIONMONITORING PROBLEM;312
7.49.4;THE DIAGNOSIS PROBLEM;312
7.49.5;EXPERIMENTAL RESULTS;313
7.49.6;CONCLUSION;314
7.49.7;REFERENCES;314
7.50;Chapter 50. NON-GAUSSIAN SMOOTHNESS PRIORAPPROACH TO IRREGULAR TIME SERIESANALYSIS;316
7.50.1;1. INTRODUCTION;316
7.50.2;2. NON GAUSSIAN MODEL AND SMOOTHING;316
7.50.3;3. NUMERICAL ALGORITHMS;317
7.50.4;4. MODEL IDENTIFICATION;318
7.50.5;5. NUMERICAL EXAMPLES AND DISCUSSIONS;318
7.50.6;6. CONCLUDING REMARKS;321
7.50.7;REFERENCES;321
7.51;Chapter 51. DETECTION OF SENSOR FAULTS BY MEANSOF MULTIVARIATE CALCULATIONMETHODS;322
7.51.1;I. INTRODUCTION;322
7.51.2;II.GENERAL VECTOR AUTOREGRESSIVE MODEL;323
7.51.3;III.REDUNDANT AUTOREGRESSIVE MODEL;325
7.51.4;CONCLUSION;326
7.51.5;REFERENCES;327
7.52;Chapter 52. STOCHASTIC STABILITY AND THE ERGODICTHEORY OF MARKOV PROCESSES WITHAPPLICATIONS TO ADAPTIVE CONTROL;328
7.52.1;I INTRODUCTION;328
7.52.2;II THE ERGODIC THEORY OF MARKOV PROCESSES;329
7.52.3;Ill AN EXAMPLE;330
7.52.4;IV CONCLUSION;332
7.52.5;REFERENCES;332
7.53;Chapter 53. SEQUENTIAL DETECTION OF CHANGES INSTOCHASTIC SYSTEMS;334
7.53.1;PROBLEM STATEMENT;334
7.53.2;CSA MODIMCATIOHS;335
7.53.3;STATISTICAL PROPERTIES OF THE MODIFIED CSA;336
7.53.4;THE PARAMETERS TUNING OF THE MODIFIED CSA;338
7.53.5;APPLICATION OF THE MODIFIED CSA TO SOME TYPICAL MODELS OF STOCHASTIC SIGNALS;338
7.53.6;REFERENCES;339
7.54;Chapter 54. A STOCHASTIC GRADIENT ALGORITHM FORMULTICHANNEL ACTIVE SOUND CONTROL;342
7.54.1;INTRODUCTION;342
7.54.2;A SINGLE CHANNEL ALGORITHM;343
7.54.3;A MULTICHANNEL ALGORITHM;344
7.54.4;CONCLUSIONS;346
7.54.5;ACKNOWLEDGEMENTS;347
7.54.6;REFERENCES;346
7.55;Chapter 55. ESTIMATION — CORRELATION, MODELINGAND IDENTIFICATION IN ADAPTIVE ARRAYPROCESSORS;348
7.55.1;INTRODUCTION;348
7.55.2;THE KNOWN COVARIANCE CASE;348
7.55.3;MATRIX REPRESENTATION OF BOUNDEDLINEAR OPERATORS;349
7.55.4;EXAMPLES OF REPRESENTATION OFDETERMINISTIC OPERATORS;350
7.55.5;MODELING AND IDENTIFYING OFSTOCHASTIC OPERATORS;350
7.55.6;AN EXAMPLE - PERIODIC SIGNALS;352
7.55.7;APPLICATION OF SINGULAR VALUEDECOMPOSITION;352
7.55.8;CONCLUSIONS;353
7.55.9;ACKNOWLEDGEMENTS;353
7.55.10;REFERENCES;353
7.56;Chapter 56. SIGN-SIGN ADAPTIVE IDENTIFIERS:CONVERGENCE AND ROBUSTNESSPROPERTIES;354
7.56.1;1. INTRODUCTION;354
7.56.2;2. PRELIMINARY OBSERVATIONS;354
7.56.3;3. CONVERGENCE FOR SMALL STEP SIZE;355
7.56.4;4. STABILITY USING ALTENATIVE LYAPUNOV FUNCTIONS;356
7.56.5;5. CONCLUSIONS;357
7.56.6;6. APPENDIX;357
7.56.7;REFERENCES;359
7.57;Chapter 57. PERSISTENCY OF EXCITATION IN POSSIBLYUNSTABLE CONTINUOUS TIME SYSTEMSAND PARAMETER CONVERGENCE INADAPTIVE IDENTIFICATION;360
7.57.1;INTRODUCTION;360
7.57.2;NOTATION;361
7.57.3;PRELIMINARY DEFINITIONS ANDPROPOSITIONS;361
7.57.4;OUTPUT REACHABILITY ANDPERSISTENCY OF EXCITATION;362
7.57.5;STATE SPACE REALIZATIONS AND PERSISTENCY OF EXCITATION;363
7.57.6;APPLICATION TO ADAPTIVE IDENTIFICATION;364
7.57.7;CONCLUSION;365
7.57.8;ACKNOWLEDGEMENTS;365
7.57.9;REFERENCES;365
7.58;Chapter 58. OPTIMAL ADAPTIVE CONTROL WITHCONSISTENT PARAMETER ESTIMATES*;366
7.58.1;INTRODUCTION;366
7.58.2;STRONG CONSISTENCY OF LSA AND SGA;367
7.58.3;ADAPTIVE LQ CONTROL WITHCONSISTENT ESTIMATION;368
7.58.4;ADAPTIVE TRACKING WITHCONSISTENT ESTIMATION;369
7.58.5;CONCLUSION;369
7.58.6;REFERENCES;370
7.59;Chapter 59. SYNCHRONOUS DATA FLOW PROGRAMMINGWITH THE LANGUAGE SIGNAL;372
7.59.1;1. INTRODUCTION.;372
7.59.2;2. CONSTRUCTION OF THE STATIC NETWORKS;373
7.59.3;3. THE TEMPORAL GENERATORS. AND THE CORRESPONDINGINSTRUCTION SET OF SIGNAL·;374
7.59.4;4. THE DEPENDENCE GRAPH OF A SIGNAL PROGRAM;375
7.59.5;5. CONCLUSION;376
7.59.6;REFERENCES;377
7.60;Chapter 60. AN ADAPTIVE MICROPHONE ARRAY IMPLEMENTED ON THE SIGNAL PROCESSOR TMS 32010;378
7.60.1;INTRODUCTION;378
7.60.2;THE REQUIREMENTS OF THE SYSTEM;378
7.60.3;THE ADAPTIVE DIRECTIONAL SYSTEM;378
7.60.4;CALIBRATIONS;379
7.60.5;MEASUREMENTS;379
7.60.6;CONCLUSIONS;380
7.60.7;REFERENCES;380
7.61;Chapter 61. ALTERNATE STRUCTURES FOR ADAPTIVETIME SERIES MODELLING;382
7.61.1;I. INTRODUCTION;382
7.61.2;II. ADAPTIVE ALGORITHMS;383
7.61.3;III. STRUCTURAL TRADE-OFFS;384
7.61.4;IV. PARALLEL STRUCTURE;384
7.61.5;V. CONCLUSION;385
7.61.6;REFERENCES;385
7.62;Chapter 62. ON ESTIMATING THE ORDER OF AN ARMAPROCESS;388
7.62.1;INTRODUCTION;388
7.62.2;PROBLEM STATEMENT;388
7.62.3;MATRIX PERTURBATION RESULTS;389
7.62.4;STATISTICAL ANALYSIS;389
7.62.5;A CLASS OF TESTS;390
7.62.6;SIMULATION RESULTS;391
7.62.7;CONCLUDING REMARKS;391
7.62.8;REFERENCES;391
7.62.9;APPENDIX: A MATRIX PERTURBATION RESULT;392
7.63;Chapter 63. OPTIMAL DIRECT ADAPTIVE CONTROLSYSTEMS WITH DELAYS;394
7.63.1;1. Introduction.;394
7.63.2;2·Problem Statement.;394
7.63.3;3·Optimal System Structure Design.;394
7.63.4;4.Optimal Predictor Model.;395
7.63.5;5.Adaptive Algorithms.;395
7.63.6;6. Optimal Adaptive Algorithms.;395
7.63.7;7. Conclusion.;396
7.63.8;References;396
7.64;Chapter 64. ADAPTIVE DEAD-TIME ESTIMATION;398
7.64.1;INTRODUCATION;398
7.64.2;PREVIOUS METHODS FOR DEAD-TIME ESTIMATION;398
7.64.3;NEW METHOD FOR DEAD-TIME ESTIMATION;399
7.64.4;EXAMPLES;399
7.64.5;CONCLUSIONS;401
7.64.6;REFERENCES;402
7.65;Chapter 65. AUTO TUNING OF THE TIME HORIZON;404
7.65.1;INTRODUCTION;404
7.65.2;EHC USING PARALLEL COMPENSATION;404
7.65.3;LEAST SQUARES PARAMETER ESTIMATION;405
7.65.4;THE AUTOTUNING ALGORITHM;406
7.65.5;SIMULATION RESULTS;407
7.65.6;SUMMARY;408
7.65.7;REFERENCES;408
7.66;Chapter 66. IMPROVEMENTS OF THE SERVOBEHAVIOUR OF THE MUSMAR SELF-TUNING CONTROLLER;410
7.66.1;INTRODUCTION;410
7.66.2;1. THE ORIGINAL MUSMAR ALGORITHM;410
7.66.3;2. THEORETICAL ANALYSIS OF THE SERVOBEHAVIOUR OF MUSMAR;411
7.66.4;3. SIMULATION RESULTS WITH MUSMAR;411
7.66.5;4. THE MODIFIED MUSMAR ALGORITHM;412
7.66.6;5. SIMULATION RESULTS WITH THE MODIFIEDMUSMAR ALGORITHM;414
7.66.7;6. COMPARISON AND CONCLUSIONS;415
7.66.8;REFERENCES;415
7.67;Chapter 67. REDUCED VARIANCE POLE-ASSIGNMENTSERVO SELF-TUNING;416
7.67.1;1. INTRODUCTION;416
7.67.2;2. A POLE-ASSIGNMENT SERVO CONTROLLER;416
7.67.3;3. REDUCED OUTPUT VARIANCE;417
7.67.4;4. MAGNITUDE OF VARIANCE REDUCTION;417
7.67.5;5. ON-LINE COST REDUCTION;418
7.67.6;6. EXTENDED SELF-TUNING CONTROL;418
7.67.7;7. A SIMULATED EXAMPLE;419
7.67.8;8. CONCLUSIONS;419
7.67.9;ACKNOWLEDGMENTS;419
7.67.10;REFERENCES;419
7.67.11;APPENDIX;420
7.68;Chapter 68. ADAPTIVE CONTROL OF LINEAR TIMEVARYINGPLANTS*;426
7.68.1;1. INTRODUCTION;426
7.68.2;2. MATHEMATICAL PRELIMINARIES;427
7.68.3;3. MODEL FOLLOWING FOR TIME-VARYINGPLANTS;427
7.68.4;4. MRAC FOR TIME-VARYING PLANTS;429
7.68.5;5. CONCLUSIONS;430
7.68.6;6. REFERENCES;430
7.68.7;APPENDIX;430
7.69;Chapter 69. NONLINEAR DYNAMICS IN ADAPTIVECONTROL: CHAOTIC AND PERIODICSTABILIZATION;432
7.69.1;1. INTRODUCTION;432
7.69.2;2. THE ADAPTIVE SCHEME;432
7.69.3;3. THE DYNAMICS OF THE CLOSED LOOP;433
7.69.4;4. THE DYNAMICS OF THE CLOSED LOOP II;434
7.69.5;5. THE DYNAMICS OF THE CLOSED LOOP III;;434
7.69.6;6. STABILITY OF THE ADAPTIVE LOOP;435
7.69.7;7. COMPLEMENTS AND CONCLUSIONS;436
7.69.8;REFERENCES;436
7.70;Chapter 70. EXPLICIT ADAPTIVE CONTROL WITHOUTPERSISTINGLY EXCITING INPUTS;438
7.70.1;1. INTRODUCTION;438
7.70.2;2. ADMISSIBLE DOMAINS IN THEPARAMETER SPACE;438
7.70.3;3. A THEOREM OF ROBUST'STABILITY FOR SLOWLY TIME VARYING SYSTEMS;439
7.70.4;4. ROBUST INDIRECT ADAPTIVE CONTROL UNDER ADMISSIBILITY HYPOTHESES;440
7.70.5;5. SOLVING THE STABILIZABILITY PROBLEM;441
7.70.6;6. CONCLUSIONS;442
7.70.7;REFERENCES;442
7.71;Chapter 71. DIRECT ADAPTIVE CONTROL OF SYSTEMSWITH BOUNDED DISTURBANCES;444
7.71.1;INTRODUCTION;444
7.71.2;II PROJECTION ALGORITHM WITH DEAD ZONE.;444
7.71.3;Ill STABILITY ANALYSIS;446
7.71.4;REFERENCES;447
7.72;Chapter 72. ENTROPY MEASURES FOR OPTIMAL ANDADAPTIVE CONTROL;448
7.72.1;INTRODUCTION;448
7.72.2;ENTROPY FORMULATION OF CONTROL PROBLEMS;449
7.72.3;EXAMPLE;450
7.72.4;CONCLUSIONS;451
7.72.5;REFERENCES;451
7.73;Chapter 73. STABILITY OF AN ADAPTIVE ARMAPREDICTOR PRESENCE OF NARROW-BANDINPUT SIGNALS;454
7.73.1;I. STABILITY OF ARMA PREDICTION;454
7.73.2;II. THEORETICAL ANALYSIS OF SELF-STABILIZATION;455
7.73.3;III. APPLICATION TO DIGITAL SPEECH CODING;457
7.73.4;IV. CONCLUSION;458
7.74;AUTHOR INDEX;460
