Optimal Sensor Networks Scheduling in Identification of Distributed Parameter Systems
Sensor networks have recently come into prominence because they hold the potential to revolutionize a wide spectrum of both civilian and military applications. An ingenious characteristic of sensor networks is the distributed nature of data acquisition. T
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Maciej Patan
Optimal Sensor Networks Scheduling in Identification of Distributed Parameter Systems
ABC
Series Advisory Board P. Fleming, P. Kokotovic, A.B. Kurzhanski, H. Kwakernaak, A. Rantzer, J.N. Tsitsiklis
Author Maciej Patan The University of Zielona Góra Poland
ISSN 0170-8643 ISBN 978-3-642-28229-4 DOI 10.1007/978-3-642-28230-0 Springer Heidelberg New York Dordrecht London
e-ISSN 1610-7411 e-ISBN 978-3-642-28230-0
Library of Congress Control Number: 2012932480 c Springer-Verlag Berlin Heidelberg 2012 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. Exempted from this legal reservation are brief excerpts in connection with reviews or scholarly analysis or material supplied specifically for the purpose of being entered and executed on a computer system, for exclusive use by the purchaser of the work. Duplication of this publication or parts thereof is permitted only under the provisions of the Copyright Law of the Publisher’s location, in its current version, and permission for use must always be obtained from Springer. Permissions for use may be obtained through RightsLink at the Copyright Clearance Center. Violations are liable to prosecution under the respective Copyright Law. 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. While the advice and information in this book are believed to be true and accurate at the date of publication, neither the authors nor the editors nor the publisher can accept any legal responsibility for any errors or omissions that may be made. The publisher makes no warranty, express or implied, with respect to the material contained herein. Printed on acid-free paper Springer is part of Springer Science+Business Media (www.springer.com)
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Preface
It is well known that the experimental setting, being an integral part of any identification experiment for a distributed physical system, significantly influences the quality of measurement data. For such systems it is usually impossible to observe their states over the entire spatial domain, therefore optimal spatial deployment of discrete sensors and their proper temporal activation scheduling, which allows estimating the unknown system parameters as accurately as possible are of fundamental significance. The precision of parameter estimation is important as parameters are often used in optimal control, environmental monitoring, industrial quality tests, fault diagnosis, or th
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