Modelling and Estimation Strategies for Fault Diagnosis of Non-Linear Systems: From Analytical to Soft Computing Approaches / Edition 1

Modelling and Estimation Strategies for Fault Diagnosis of Non-Linear Systems: From Analytical to Soft Computing Approaches / Edition 1

by Marcin Witczak
ISBN-10:
3540711147
ISBN-13:
9783540711148
Pub. Date:
05/18/2007
Publisher:
Springer Berlin Heidelberg
ISBN-10:
3540711147
ISBN-13:
9783540711148
Pub. Date:
05/18/2007
Publisher:
Springer Berlin Heidelberg
Modelling and Estimation Strategies for Fault Diagnosis of Non-Linear Systems: From Analytical to Soft Computing Approaches / Edition 1

Modelling and Estimation Strategies for Fault Diagnosis of Non-Linear Systems: From Analytical to Soft Computing Approaches / Edition 1

by Marcin Witczak

Paperback

$109.99
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Overview

This monograph presents a variety of techniques that can be used for designing robust fault diagnosis schemes for non-linear systems. The introductory part of the book is of a tutorial value and can be perceived as a good starting point for the new-comers to this field. Subsequently, advanced robust observer structures are presented. Parameter estimation based techniques are discussed as well. A particular attention is drawn to experimental design for fault diagnosis. The book also presents a number of robust soft computing approaches utilizing evolutionary algorithms and neural networks. All approaches described in this book are illustrated by practical applications.


Product Details

ISBN-13: 9783540711148
Publisher: Springer Berlin Heidelberg
Publication date: 05/18/2007
Series: Lecture Notes in Control and Information Sciences , #354
Edition description: 2007
Pages: 212
Product dimensions: 6.10(w) x 9.25(h) x 0.02(d)

Table of Contents

I. Principles of Fault Diagnosis.- Analytical Techniques-Based FDI.- Soft Computing-Based FDI.- II. State and Parameter Estimation Strategies.- State Estimation Techniques for FDI.- Parameter Estimation-Based FDI.- III. Soft Computing Strategies.- Evolutionary Algorithms.- Neural Networks.- Conclusions and Future Research Directions.
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