Isermann System Identification

Tutorials Presented at the 5th IFAC Symposium on Identification and System Parameter Estimation, F.R. Germany, September 1979
1. Auflage 2014
ISBN: 978-1-4831-3945-6
Verlag: Elsevier Science & Techn.
Format: PDF
Kopierschutz: 1 - PDF Watermark

E-Book, Englisch, 91 Seiten, Web PDF

System Identification is a special section of the International Federation of Automatic Control (IFAC)-Journal Automatica that contains tutorial papers regarding the basic methods and procedures utilized for system identification. Topics include modeling and identification; step response and frequency response methods; correlation methods; least squares parameter estimation; and maximum likelihood and prediction error methods. After analyzing the basic ideas concerning the parameter estimation methods, the book elaborates on the asymptotic properties of these methods, and then investigates the application of the methods to particular model structures. The text then discusses the practical aspects of process identification, which includes the usual, general procedures for process identification; selection of input signals and sampling time; offline and on-line identification; comparison of parameter estimation methods; data filtering; model order testing; and model verification. Computer program packages are also discussed. This compilation of tutorial papers aims to introduce the newcomers and non-specialists in this field to some of the basic methods and procedures used for system identification.

Autoren/Hrsg.

Isermann, R.

Inhaltsverzeichnis

1;Front Cover;1
2;System Identification;4
3;Copyright Page;5
4;Table of Contents;6
5;Preface;8
6;Chapter 1. Principles of Model Building and Identification;10
6.1;1. WHAT IS MODEL BUILDING?;10
6.2;2. HOW TO DESCRIBE A DYNAMIC SYSTEM MATHEMATICALLY;12
6.3;3. THEORETICAL MODELLING;17
6.4;4. EXPERIMENTAL ANALYSIS: IDENTIFICATION;20
6.5;5. MODEL BUILDING BY COMBINING THEORETICAL AND EXPERIMENTAL ANALYSIS;21
6.6;6. CONCLUSIONS;22
6.7;REFERENCES;22
7;Chapter 2. Step Response and Frequency Response Methods;24
7.1;INTRODUCTION;24
7.2;METHODS FOR NONPERIODIC TEST SIGNALS;25
7.3;METHODS FOR PERIODIC TEST SIGNAL;29
7.4;CONCLUSION;31
7.5;REFERENCES;31
8;Chapter 3. Correlation Methods;32
8.1;1. INTRODUCTION;32
8.2;2. STOCHASTIC PROCESSES;32
8.3;3. PROPERTIES OF AUTOCORRELATION FUNCTIONS;33
8.4;4. ANALYTICAL COMPUTATION OF SOME AUTOCORRELATION FUNCTIONS;33
8.5;5. DETERMINATION OF CORRELATION FUNCTIONS OF DATA;35
8.6;6. PSEUDO-RANDOM BINARY SIGNALS;36
8.7;7. DETERMINATION OF SYSTEM WEIGHTING FUNCTION USING P.R.B.S.;36
8.8;8. SPECTRAL ANALYSIS;37
8.9;9. APPLICATIONS OF CORRELATION;38
8.10;10. CONCLUSIONS;39
8.11;REFERENCES;39
9;Chapter 4. Least Squares Parameter Estimation;40
9.1;1. INTRODUCTION;40
9.2;2. BASIC RELATIONS;40
9.3;3. ANALYTIC SOLUTION OF THE LEAST SQUARES;43
9.4;4. RECURSIVE SOLUTION OF THE LEAST SQUARES;43
9.5;5. INSTRVMENTAL VARIABLE METHOD—IV;44
9.6;6. GENERALIZED LEAST SQUARES—GLS;45
9.7;7. EXTENDED LEAST SQUARES—ELS;47
9.8;8. DISCRETE SQUARE ROOT FILTERING;48
9.9;9. MODIFIED SQUARE ROOT FILTERING;52
9.10;10. COMPLEMENTARY REMARKS;54
9.11;11. CONCLUSIONS;54
9.12;REFERENCES;54
10;Chapter 5. Maximum Likelihood and Prediction Error Methods;56
10.1;1. INTRODUCTION;56
10.2;2. THE MAXIMUM LIKELIHOOD METHOD;57
10.3;3. ESTIMATING PARAMETERS IN DYNAMICAL SYSTEMS;60
10.4;4. ESTIMATION THEORY;67
10.5;5. INTERACTIVE COMPUTING;70
10.6;6. PRACTICAL ASPECTS;73
10.7;REFERENCES;78
11;Chapter 6. Practical Aspects of Process Identification;80
11.1;1. INTRODUCTION;80
11.2;2. SELECTION OF INPUT SIGNALS;82
11.3;3. SELECTION OF SAMPLING TIME;84
11.4;4. OFF-LINE AND ON-LINE IDENTIFICATION;85
11.5;5. COMPARISON OF PARAMETER-ESTIMATION METHODS;86
11.6;6. DATA FILTERING;88
11.7;7. MODEL ORDER TESTING AND MODEL VERIFICATION;89
11.8;8. PROGRAM PACKAGES FOR PROCESS IDENTIFICATION;91
11.9;9. CONCLUDING REMARKS;92
11.10;REFERENCES;92