Identification of continuous systems:
Gespeichert in:
| Hauptverfasser: | , |
|---|---|
| Format: | Buch |
| Sprache: | English |
| Veröffentlicht: |
Amsterdam u.a.
North-Holland
1987
|
| Schriftenreihe: | North-Holland systems and control series
10 |
| Schlagworte: | |
| Online-Zugang: | Inhaltsverzeichnis |
| Beschreibung: | XV, 378 S. |
| ISBN: | 0444703160 |
Internformat
MARC
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| 245 | 1 | 0 | |a Identification of continuous systems |c Heinz Unbehauen and Ganti Prasada Rao |
| 264 | 1 | |a Amsterdam u.a. |b North-Holland |c 1987 | |
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| 490 | 1 | |a North-Holland systems and control series |v 10 | |
| 650 | 4 | |a Estimation paramétrique | |
| 650 | 4 | |a Fonction transfert | |
| 650 | 4 | |a Identification système | |
| 650 | 4 | |a Modèle adaptatif | |
| 650 | 4 | |a Modèle non paramétrique | |
| 650 | 4 | |a Système continu | |
| 650 | 4 | |a Système dynamique continu | |
| 650 | 4 | |a Système entrée multiple | |
| 650 | 4 | |a Système sortie multiple | |
| 650 | 7 | |a Systèmes - Identification |2 ram | |
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Datensatz im Suchindex
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|---|---|
| adam_text | Titel: Identification of continuous systems
Autor: Unbehauen, Heinz
Jahr: 1987
V TABLE OF CONTENTS PREFACE XIII ACKNOWLEDGMENTS XV CHAPTER I INTRODUCTION 1 1.1 System Identification and Continuous Models 1 1.2 Identification and Parameter Estimation 4 1.3 A Brief Overview of the Field 5 1.3.1 Nonparametric methods 7 1.3.2 Parametric methods 7 1.3.3 Systems with nonlinear, time-varying and time- delay elements and system structure 12 1.3.4 Distributed parameter systems 13 1.4 Scope of the Book 14 CHAPTER 2 CONTINUOUS-TIME MODELS OF DYNAMICAL 23 SYSTEMS 2.1 Nonparametric Models 24 2.1.1 Linear time-invariant systems (LTIVS) 24 2.1.2 Linear time-varying systems (LTVS) 26 2.1.3 Nonlinear systems (NLS) 26 2.2 Parametric Models 28 2.2.1 Linear time-invariant (LTIV) systems 28 2.2.1.1 State space models 28 2.2.1.2 The weighting matrix of LTIV systems 29 2.2.1.3 Solution in frequency-domain 30 2.2.1.4 Canonical forms for LTIV systems 31 2.2.1.5 Diagonalization of the system matrix 35 2.2.1.6 Controllability and observability 38 2.2.2 Linear time-varying (LTV) systems, nonlinear systems and delay systems 38
VI Table of Contents 2.2.2.1 Zadeh’s system function 39 2.2.2.2 State space representation of LTV systems 40 2.2.2.3 Solution of the state equations of LTV systems 41 2.2.2.4 Transformation of state equations 42 2.2.2.5 Systems with separability properties 43 2.2.2.6 Systems with separable nonlinear elements 44 2.2.2.7 Systems containing time-delays 45 2.2.2.8 Some useful methods of parametrization of nonlinear and time-varying models 45 2.3 Stochastic Models of Linear Time-Invariant Systems 47 2.3.1 The state space model 47 2.3.2 The transfer function matrix model 47 2.3.3 The special ’innovations’ Kalman filter 47 2.4 Models of Distributed Parameter Systems (DPS) 48 CHAPTER 3 SIGNALS AND THEIR REPRESENTATIONS 51 3.1 Introduction 51 3.1.1 Time/frequency-domain descriptions 51 3.1.1.1 One-sided Laplace transform 51 3.1.1.2 Two-sided Laplace transform 52 3.1.1.3 Fourier tranform 53 3.1.1.4 One-sided z-transform 53 3.1.1.5 Two-sided z-transform 54 3.1.1.6 Discrete Fourier Transform (DFT) 55 3.1.1.7 Fast Fourier Transform (FFT) 55 3.1.2 Generalized functions or distributions 55 3.2 Functions in the Ordinary Sense 56 3.2.1 Functions on an orthogonal basis 56 3.2.1.1 Countable basis 56 3.2.2 Systems of orthogonal polynomials 58 3.2.2.1 Shifting and scaling the standard systems 70 3.2.2.2 Least squares approximation 70 3.2.3 Systems of piecewise constant basis-functions (PCBF) 70 3.2.3.1 Block-pulse functions (BPF) 71
Table of Contents VII 3.2.3.2 Rademacher functions (RF) 71 3.2.3.3 Walsh functions (WF) 71 3.2.3.4 Haar functions (HF) 75 3.2.4 Multi-dimensional expansions in terms of systems of orthogonal functions 77 3.2.5 Time-and frequency-domain descriptions of stochastic signals 81 3.2.5.1 Some important properties of correlation functions 81 3.2.5.2 Some examples of power density spectra 83 3.3 Distribution or Generalized Functions 85 3.3.1 The Poisson moment functionals (PMF) in one dimension 85 3.3.2 Multi-dimensional Poisson moment functionals (MDPMF) 85 CHAPTER 4 IDENTIFICATION OF LINEAR TIME-INVARIANT (LTTV) SYSTEMS VIA NONPARAMETRIC MODELS 89 4.1 The Role of Nonparametric Models in Continuous System Identification 89 4.2 Test Signals for System Identification 90 4.2.1 Some important deterministic signals 90 4.2.2 Some important random signals 92 4.2.2.1 Random telegraph signal 92 4.2.2.2 Quantized binary random signal 93 4.2.2.3 Quantized binary and ternary pseudorandom signals 94 4.3 Identification of Linear Time-Invariant Systems - Time-Domain Approach 97 4.3.1 Step/Impulse response measurement 97 4.3.1.1 Measurements using a block-pulse input 97 4.3.1.2 Measurements using a saturated ramp function (time integral of block-pulse function) input 98 4.3.1.3 Measurements using an arbitrary deterministic signal 99 4.3.2 Impulse response estimation by correlation methods - The stochastic approach 101
VIII Table of Contents 4.3.2.1 Evaluation of impulse response or weighting function 101 4.3.2.2 Correlation analysis with binary and ternary random signals 104 4.3.2.3 Numerical solution of the basic equation 109 4.4 Identification of Linear Time-Invariant Systems - Frequency-Domain Approach 110 4.4.1 Power spectral densities and correlation functions 110 4.4.1.1 Basic definitions and numerical evaluation 110 4.4.1.2 Coherence function 115 4.4.1.3 The periodogram 116 4.4.2 Identification of a system in closed-loop 117 4.4.3 Direct determination of frequency response by correlation 119 4.5 Methods for Obtaining Transfer Functions from Nonparametric Models 121 4.5.1 From nonparametric models in time-domain to transfer functions 121 4.5.1.1 The method of flexion tangents and times required to reach certain percent (of steady state) values 121 4.5.1.2 The method of moments 136 4.5.2 From nonparametric models in frequency- domain to transfer functions 137 4.5.2.1 Method of Bode asymptotes 138 4.5.2.2 Approximation of given frequency response to transfer function in rational form 139 4.5.2.3 Least squares approaches for transfer function synthesis from frequency response data 143 4.6 Numerical Transformations between Time- and Frequency-Domains 151 4.6.1 Basic relations 151 4.6.2 Determination of frequency response from step response 155
Table of Contents IX 4.6.3 Extension to the case of input signals other than step functions 157 4.6.4 Determination of step response from frequency response 160 CHAPTER 5 PARAMETER ESTIMATION FOR CONTINUOUSTIME MODELS 167 5.1 Introduction 167 5.2 The Primary Stage 170 5.2.1 An introductory example 170 5.2.2 The method (modulating) function technique 172 5.2.3 The Poisson moment functional (PMF) method 173 5.2.4 Method of orthogonal funtions 175 5.2.5 Identification of lumped linear time-invariant SISO systems 177 5.2.5.1 The PMF algorithm (Method 2) 177 5.2.5.2 The orthogonal function method 182 5.2.5.3 The method of linear filters 193 5.2.6 Remarks 199 5.3 The Secondary Stage: Parameter Estimation 199 5.3.1 Scheme for parameter estimation and model structures 199 5.3.2 The least squares (LS-) method 205 5.3.2.1 Direct solution 205 5.3.2.2 Recursive solution 208 5.3.3 The instrumental variable (IV-) method 211 5.3.4 The maximum likelihood (ML-) method 214 5.3.5 Weighted parameter estimation 218 5.3.6 Normalized PMF’s 220 5.3.7 Examples 221 CHAPTER 6 IDENTIFICATION OF LINEAR SYSTEMS USING ADAPTIVE MODELS 237 6.1 Model Adaptation via Gradient Methods 238 6.1.1 The parallel model approach 238 6.1.2 The series (reciprocal) model approach 245 6.1.3 The series-parallel model approach 247
X Table of Contents 6.1.4 Stability of model adaptation using gradient methods 250 6.2 Model adaptation in frequency-domain 253 6.3 Model adaptation using stability theory 258 6.3.1 The method based on Liapunov’s stability theory 258 6.3.1.1 The basics of the technique 258 6.3.1.2 A general design method for the series-parallel model approach 260 6.3.1.3 A general design method for the parallel model approach 264 6.3.2 The model based on hyperstability theory 267 6.3.2.1 A brief introduction to hyperstability theory 267 6.3.2.2 Stable identification with adaptive models on the basis of hyperstability theory 275 6.4 Model adaptation using linear filters 283 6.4.1 The method based on Liapunov’s stability theory 283 6.4.2 The method based on hyperstability theory 289 CHAPTER 7 IDENTIFICATION OF MULTI-INPUT MULTI-OUTPUT (MIMO) SYSTEMS, DISTRIBUTED PARAMETER SYSTEMS (DPS) AND SYSTEMS WITH UNKNOWN DELAYS AND NONLINEAR ELEMENTS 299 7.1 Multi-input multi-output (MIMO) systems 299 7.1.1 The total (or MIMO) model 299 7.1.2 The MISO model decomposition 301 7.1.3 The SISO model decomposition 303 7.1.4 General formulation of recursive algorithm for MISO models 304 7.1.5 The Poisson moment functional (PMF) algorithm 306 7.1.6 The orthogonal functions method 307 7.2 Time-varying parameter systems (TYPS) 311 7.2.1 A simple example for illustration 311 7.2.2 The general algorithm 314 7.3 Lumped systems with unknown time-delays 319
Table of Contents XI 7.3.1 The output error approach 319 7.3.2 The equation error approach 321 7.3.3 The iterative shift algorithm (ISA) 323 7.3.4 Identification when the unknown delay is known to be small 327 7.4 Identification of systems with unknown nonlinear elements 330 7.4.1 The PMF approach 331 7.4.2 The orthogonal functions approach 332 7.4.3 Identification of systems with piecewise linear models 333 7.5 Identification of distributed parameter systems (DPS) 336 7.5.1 The multi-dimensional PMF approach 337 7.5.2 The use of multi-dimensional systems of orthogonal functions 341 7.6 Determination of system structure 349 7.6.1 Matrix rank methods (MRM) 349 7.6.2 Parameter error function approach 352 Notation and Symbols 361 Author Index 363 Subject Index 367
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| any_adam_object | 1 |
| author | Unbehauen, Heinz 1935-2019 Rao, Ganti Prasada |
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| indexdate | 2024-07-09T15:18:48Z |
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| isbn | 0444703160 |
| language | English |
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| physical | XV, 378 S. |
| publishDate | 1987 |
| publishDateSearch | 1987 |
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| publisher | North-Holland |
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| series | North-Holland systems and control series |
| series2 | North-Holland systems and control series |
| spelling | Unbehauen, Heinz 1935-2019 Verfasser (DE-588)107151634 aut Identification of continuous systems Heinz Unbehauen and Ganti Prasada Rao Amsterdam u.a. North-Holland 1987 XV, 378 S. txt rdacontent n rdamedia nc rdacarrier North-Holland systems and control series 10 Estimation paramétrique Fonction transfert Identification système Modèle adaptatif Modèle non paramétrique Système continu Système dynamique continu Système entrée multiple Système sortie multiple Systèmes - Identification ram Théorie signal System identification Kontinuierliches System (DE-588)4263504-4 gnd rswk-swf Systemidentifikation (DE-588)4121753-6 gnd rswk-swf Dynamisches System (DE-588)4013396-5 gnd rswk-swf Systemidentifikation (DE-588)4121753-6 s Kontinuierliches System (DE-588)4263504-4 s DE-604 Dynamisches System (DE-588)4013396-5 s Rao, Ganti Prasada Verfasser aut North-Holland systems and control series 10 (DE-604)BV000003991 10 HBZ Datenaustausch application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=000466757&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Unbehauen, Heinz 1935-2019 Rao, Ganti Prasada Identification of continuous systems North-Holland systems and control series Estimation paramétrique Fonction transfert Identification système Modèle adaptatif Modèle non paramétrique Système continu Système dynamique continu Système entrée multiple Système sortie multiple Systèmes - Identification ram Théorie signal System identification Kontinuierliches System (DE-588)4263504-4 gnd Systemidentifikation (DE-588)4121753-6 gnd Dynamisches System (DE-588)4013396-5 gnd |
| subject_GND | (DE-588)4263504-4 (DE-588)4121753-6 (DE-588)4013396-5 |
| title | Identification of continuous systems |
| title_auth | Identification of continuous systems |
| title_exact_search | Identification of continuous systems |
| title_full | Identification of continuous systems Heinz Unbehauen and Ganti Prasada Rao |
| title_fullStr | Identification of continuous systems Heinz Unbehauen and Ganti Prasada Rao |
| title_full_unstemmed | Identification of continuous systems Heinz Unbehauen and Ganti Prasada Rao |
| title_short | Identification of continuous systems |
| title_sort | identification of continuous systems |
| topic | Estimation paramétrique Fonction transfert Identification système Modèle adaptatif Modèle non paramétrique Système continu Système dynamique continu Système entrée multiple Système sortie multiple Systèmes - Identification ram Théorie signal System identification Kontinuierliches System (DE-588)4263504-4 gnd Systemidentifikation (DE-588)4121753-6 gnd Dynamisches System (DE-588)4013396-5 gnd |
| topic_facet | Estimation paramétrique Fonction transfert Identification système Modèle adaptatif Modèle non paramétrique Système continu Système dynamique continu Système entrée multiple Système sortie multiple Systèmes - Identification Théorie signal System identification Kontinuierliches System Systemidentifikation Dynamisches System |
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