Optimal Fault Detection of a Class of Nonlinear Systems
Having investigated the existence conditions and parameterisation of nonlinear observer-based fault detection systems in the previous two chapters, we now devote our attention to the solution of the optimal fault detection problem formulated in Definition
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Advanced Methods for Fault Diagnosis and Fault-tolerant Control
Advanced Methods for Fault Diagnosis and Fault-tolerant Control
Steven X. Ding
Advanced Methods for Fault Diagnosis and Fault-tolerant Control
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Steven X. Ding Universität Duisburg-Essen Duisburg, Germany
ISBN 978-3-662-62003-8 ISBN 978-3-662-62004-5 (eBook) https://doi.org/10.1007/978-3-662-62004-5 © Springer-Verlag GmbH Germany, part of Springer Nature 2021 This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, 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. The publisher, the authors and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, expressed or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. Responsible Editor: Michael Kottusch This Springer imprint is published by the registered company Springer-Verlag GmbH, DE part of Springer Nature. The registered company address is: Heidelberger Platz 3, 14197 Berlin, Germany
To My Parents and Eve Limin
Preface
This book is the third one in my book series plan. While the first two are dedicated to model-based and data-driven fault diagnosis respectively, this one addresses topics in both model-based and data-driven thematic fields, and increasingly focuses on fault-tolerant control issues and application of machine learning methods. The enthusiasm for machine learning and big data technologies has considerable influences on the development of fault diagnosis techniques in recent years. It seems that research efforts in the thematic domain of data-driven fault diagnosis gradually become a competition under the Olympic motto, faster transferring machine learning methods to fault diagnosis applications, preferably adopting higher actual (most popular) machine learning methods, and stronger publishing. The main intention of this book is to study basic fault diagnosis and fault-tolerant control problems, which build a framework for long-term research efforts in the fault diagnosis and fault-tolerant control domain. In this framework, possibly unified solutions and methods can be developed for general classes of systems. This book i
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