Cover image for Modelling and parameter estimation of dynamic systems
Title:
Modelling and parameter estimation of dynamic systems
Series:
IEE control engineering series ; 65
Publication Information:
Stevenage, Herts : The Institution Of Electrical Engineers, 2004
ISBN:
9780863413636
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30000010159339 TA168 R364 2004 Open Access Book Book
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Summary

Summary

Parameter estimation is the process of using observations from a system to develop mathematical models that adequately represent the system dynamics. The assumed model consists of a finite set of parameters, the values of which are calculated using estimation techniques. Most of the techniques that exist are based on least-square minimisation of error between the model response and actual system response. However, with the proliferation of highspeed digital computers, elegant and innovative techniques like filter error method, genetic algorithms and artificial neural networks are finding more and more use in parameter estimation problems. Modelling and Parameter Estimation of Dynamic Systems presents a detailed examination of many estimation techniques and modelling problems.


Table of Contents

Introduction
Least Squares Methods
Output Error Methods
Filtering Methods
Filter Error
Method Determination of Model
Order and Structure
Estimation Before Modelling Approach (EBM)
Approach Based on a Concept of Model Error Parameter
Estimation Approaches for Unstable/Augmented Systems Parameter
Estimation using ANN and Genetic Algorithms Online Parameter Estimation
Summary
Appendix A Properties of Signals, Matrices, Estimators and Estimates
Appendix B Aircraft Derivative Models for Parameter Estimation