Modelling and Estimation Strategies for Fault Diagnosis of Non-Linear Systems
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-
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Marcin Witczak
Modelling and Estimation Strategies for Fault Diagnosis of Non-Linear Systems From Analytical to Soft Computing Approaches
ABC
Series Advisory Board F. Allgöwer, P. Fleming, P. Kokotovic, A.B. Kurzhanski, H. Kwakernaak, A. Rantzer, J.N. Tsitsiklis
Author Dr. Marcin Witczak Institute of Control and Computation Engineering University of Zielona Góra Ul. Podgórna 50 65-246 Zielona Góra Poland E-mail: [email protected]
Library of Congress Control Number: 2007922361 ISSN print edition: 0170-8643 ISSN electronic edition: 1610-7411 ISBN-10 3-540-71114-7 Springer Berlin Heidelberg New York ISBN-13 978-3-540-71114-8 Springer Berlin Heidelberg New York This work is subject to copyright. All rights are reserved, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilm or in any other way, and storage in data banks. Duplication of this publication or parts thereof is permitted only under the provisions of the German Copyright Law of September 9, 1965, in its current version, and permission for use must always be obtained from Springer. Violations are liable for prosecution under the German Copyright Law. Springer is a part of Springer Science+Business Media springer.com c Springer-Verlag Berlin Heidelberg 2007 The use of general descriptive names, registered names, trademarks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. Typesetting: by the authors and SPS using a Springer LATEX macro package Printed on acid-free paper
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Preface
It is well known that there is an increasing demand for modern systems to become safer and reliable. This real world’s development pressure has transformed fault diagnosis, initially perceived as the art of designing a satisfactorily safe system, into the modern science that it is today. Indeed, the classic way of fault diagnosis boils down to controlling the limits of single variables and then using the resulting knowledge for fault-alarm purposes. Apart from the simplicity of such an approach, the observed increasing complexity of modern systems necessitates the development of new fault diagnosis techniques. Such a development can only be realised by taking into account the information hidden in all measurements. One way to tackle such a challenging problem is to use the so-called model-based approach. Indeed, the application of an adequate model of the system being supervised is very profitable with respect to gaining the knowledge regarding its behaviour. A further and deeper understanding of the current system behaviour can be achieved by implementing parameter and state estimation strategies. The obtained estimates can then be used for supporting diagnostic decisions. Although the majority of industrial systems are non-linear in their nature, the most
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