Trends and Progress in System Identification (eBook)

Ifac Series for Graduates, Research Workers & Practising Engineers

Pieter Eykhoff (Herausgeber)

eBook Download: PDF

2014 | 1. Auflage
418 Seiten
Elsevier Science (Verlag)
978-1-4831-4866-3 (ISBN)

Infos

Trends and Progress in System Identification is a three-part book that focuses on model considerations, identification methods, and experimental conditions involved in system identification. Organized into 10 chapters, this book begins with a discussion of model method in system identification, citing four examples differing on the nature of the models involved, the nature of the fields, and their goals. Subsequent chapters describe the most important aspects of model theory; the ''classical'' methods and time series estimation; application of least squares and related techniques for the estimation of dynamic system parameters; the maximum likelihood and error prediction methods; and the modern development of statistical methods. Non-parametric approaches, identification of nonlinear systems by piecewise approximation, and the minimax identification are then explained. Other chapters explore the Bayesian approach to system identification; choice of input signals; and choice and effect of different feedback configurations in system identification. This book will be useful for control engineers, system scientists, biologists, and members of other disciplines dealing withdynamical relations.

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Trends and Progress in System Identification is a three-part book that focuses on model considerations, identification methods, and experimental conditions involved in system identification. Organized into 10 chapters, this book begins with a discussion of model method in system identification, citing four examples differing on the nature of the models involved, the nature of the fields, and their goals. Subsequent chapters describe the most important aspects of model theory; the "e;"e;classical"e;"e; methods and time series estimation; application of least squares and related techniques for the estimation of dynamic system parameters; the maximum likelihood and error prediction methods; and the modern development of statistical methods. Non-parametric approaches, identification of nonlinear systems by piecewise approximation, and the minimax identification are then explained. Other chapters explore the Bayesian approach to system identification; choice of input signals; and choice and effect of different feedback configurations in system identification. This book will be useful for control engineers, system scientists, biologists, and members of other disciplines dealing withdynamical relations.

Inhalt

Front Cover 
1 
Trends and Progress in System Identification 
4 
Copyright Page 
5 
Table of Contents 
6 
Contributors 14
Chapter 0. PROLOGUE 
18 
REFERENCES 21
Chapter 1. THE MODEL METHOD 
22 
1. NECESSITY OF MODELING 22
2. PRINCIPLES OF THE MODEL METHOD 23
3. PHASES IN THE ELABORATION OF A MODEL 24
4. EXAMPLES 26
5. WHERE ARE THE DIFFICULTIES? 
43 
6. CONCLUSION 44
REFERENCES 44
Chapter 2. MODELS: EQUIVALENCES, USES, EXTENSIONS 
46 
1. INTRODUCTION 46
2. A "GEDANKEN-EXPERIMENT" 46
3. MINIMAL SINGLE-INPUT, SINGLE OUTPUT MODELS 
50 
4. MINIMAL MULTI-INPUT, MULTI-OUTPUT MODELS 
55 
5. EXTENSION OF MODEL CARRIERS 66
6. EXTENSIONS OF MODEL STRUCTURE 69
7. CONCLUSIONS 76
ACKNOWLEDGEMENTS 76
REFERENCES 77
Chapter 3. "CLASSICAL" METHODS AND TIME SERIES ESTIMATION 
84 
1. "CLASSICAL" METHODS 84
2. TIME SERIES ESTIMATION 101
References 118
Chapter 4. LEAST SQUARES AND REGRESSION METHODS 
120 
1 BASIC CONCEPT 120
2 RECURSIVE SOLUTION OF THE LEAST SQUARES 
127 
3 KALMAN-BUCY FILTERING 
130 
4 EXTENSION OF RECURSIVE ALGORITHMS 
137 
5 DISCRETE SQUARE ROOT FILTERING 
143 
6 APPLICATIONS OF LEAST SQUARES 148
REFERENCES 158
Chapter 5. MAXIMUM LIKELIHOOD AND PREDICTION ERROR METHODS 
162 
1. INTRODUCTION 162
2. THE MAXIMUM LIKELIHOOD METHOD 163
3. ESTIMATING PARAMETERS IN DYNAMICAL SYSTEMS 
166 
4. ESTIMATION THEORY 172
5. INTERACTIVE COMPUTING 175
6. PRACTICAL ASPECTS 179
REFERENCES 184
Chapter 6. MODERN DEVELOPMENT OF STATISTICAL METHODS 
186 
1. INTRODUCTION 186
2. THE BASIC MODEL 186
3. THE CRITERION 187
4. AIC AS AN ESTIMATE OF NEG-ENTROPY 
187 
5. IMPLICATIONS OF MAICE FOR IDENTIFICATION 
190 
6. PRACTICAL APPLICATIONS 191
7. INSTRUMENTAL MODELS 194
8. RELATION WITH OTHER PROCEDURES 195
9. FURTHER DEVELOPMENT 196
10. CONCLUSION 199
ACKNOWLEDGEMENT 199
REFERENCES 199
Chapter 7. EXTENSIONS TO NONLINEAR AND MINIMAX APPROACHES 
202 
1. NONPARAMETRIC APPROACHES 202
2. IDENTIFICATION OF NONLINEAR PROCESSES BY PIECEWISE APPROCIMATION.* 
213 
3. THE MINIMAX APPROACH IN IDENTIFICATION 
230 
REFERENCES 238
Appendix I 
241 
Appendix II 
246 
Chapter 8. BAYESIAN APPROACH TO SYSTEM IDENTIFICATION 
256 
1 INTRODUCTION 256
2 UNDERLYING PHILOSOPHY AND BASIC RELATIONS 
257 
3 SYSTEM MODEL, REEXAMINED FROM BAYSIAN VIEWPOINT 
262 
4 PARAMETER ESTIMATION AND OUTPUT PREDICTION 
270 
5 TIME-VARYING PARAMETERS AND ADAPTIVITY 
298 
6 SYSTEM CLASSIFICATION 306
APPENDICES A Some Useful Lemmas from Matrix Algebra and Integral Calculus 
318 
APPENDICES . FORTRAN Subroutine REFIL 
319 
REFERENCES 320
Chapter 9. CHOICE OF INPUT SIGNALS 
322 
1. INTRODUCTION 322
2. HISTORICAL BACKGROUND 323
3. STATEMENT OF THE PROBLEM 324
4. INPUT DESIGN CRITERIA 325
5. TIME-DOMAIN SYNTHESIS OF OPTIMAL INPUTS 
327 
6. FREQUENCY-DOMAIN SYNTHESIS OF OPTIMAL INPUTS 
335 
7. EXTENSIONS 337
8. EXAMPLES 340
9. CONCLUSIONS 381
REFERENCES 381
Chapter 10. CHOICE AND EFFECT OF DIFFERENT FEEDBACK CONFIGURATIONS 
384 
1. INTRODUCTION 384
2. BASIC CONCEPTS 384
3. IDENTIFIABILITY AND MEASURES OF ACCURACY 
388 
4. INFLUENCE OF THE IDENTIFICATION METHOD ON IDENTIFIABILITY AND ACCURACY 
390 
5. INFLUENCE OF THE MODEL STRUCTURE ON IDENTIFIABILITY AND ACCURACY 
392 
6. INFLUENCE OF FEEDBACK ON IDENTIFIABILITY AND ACCURACY 
393 
7. APPLICATIONS 400
8. CONCLUSIONS 402
Acknowledgments. 403
REFERENCES 403
EPILOGUE 406
AUTHOR INDEX 410
SUBJECT INDEX 416

Produkt-Details

• Erscheint lt. Verlag: 20.5.2014
• Sprache: englisch
• Themenwelt: Mathematik / Informatik ► Informatik ► Theorie / Studium
• Themenwelt: Mathematik / Informatik ► Mathematik ► Analysis
• Themenwelt: Naturwissenschaften
• Themenwelt: Technik ► Bauwesen
• ISBN-10: 1-4831-4866-1 / 1483148661
• ISBN-13: 978-1-4831-4866-3 / 9781483148663