Fault Diagnosis of Nonlinear Systems Using a Hybrid Approach
There is an increasing demand for man-made dynamical systems to operate autonomously in the presence of faults and failures in sensors, actuators or components. Fault diagnosis and health monitoring are essential components of an autonomous system. Hence,
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Ehsan Sobhani-Tehrani, Khashayar Khorasani
Fault Diagnosis of Nonlinear Systems Using a Hybrid Approach
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Series Advisory Board P. Fleming, P. Kokotovic, A.B. Kurzhanski, H. Kwakernaak, A. Rantzer, J.N. Tsitsiklis
Authors Ehsan Sobhani-Tehrani GlobVision, Inc. 100 Bd. Alexis Nihon Saint-Laurent QC H4M 2N9 Suite 465 Canada [email protected]
Khashayar Khorasani Concordia University Department of Electrical & Computer Engineering 1455 Maisonneuve Blvd. West, EV005.126 Montreal QC H3G 1M8 Canada [email protected]
ISBN 978-0-387-92906-4 e-ISBN 978-0-387-92907-1 DOI 10.1007/978-0-387-92907-1 Springer Dordrecht Heidelberg London New York Lecture Notes in Control and Information Sciences
ISSN 0170-8643
Library of Congress Control Number: 2009921650 c Springer Science+Business Media, LLC 2009 All rights reserved. This work may not be translated or copied in whole or in part without the written permission of the publisher (Springer Science+Business Media, LLC, 233 Spring Street, New York, NY 10013, USA), except for brief excerpts in connection with reviews or scholarly analysis. Use in connection with any form of information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed is forbidden. The use in this publication of trade names, trademarks, service marks, and similar terms, even if they are not identified as such, is not to be taken as an expression of opinion as to whether or not they are subject to proprietary rights. Printed on acid-free paper Springer is part of Springer Science+Business Media (www.springer.com)
To Zahra and Ahmad, my parents, for their unwavering love Ehsan Sobhani-Tehrani
Preface
The increasing complexity of space vehicles such as satellites, and the cost reduction measures that have affected satellite operators are increasingly driving the need for more autonomy in satellite diagnostics and control systems. Current methods for detecting and correcting anomalies onboard the spacecraft as well as on the ground are primarily manual and labor intensive, and therefore, tend to be slow. Operators inspect telemetry data to determine the current satellite health. They use various statistical techniques and models, but the analysis and evaluation of the large volume of data still require extensive human intervention and expertise that is prone to error. Furthermore, for spacecraft and most of these satellites, there can be potentially unduly long delays in round-trip communications between the ground station and the satellite. In this context, it is desirable to have onboard fault-diagnosis system that is capable of detecting, isolating, identifying or classifying faults in the system without the involvement and intervention of operators. Toward this end, the principle goal here is to improve the efficiency, accuracy, and reliability of the trend analysis and diagnostics techniques through utilization of intelligent-based and hybrid-based methodologies. It is a well-recognized fact that an
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