Fault Detection and Flight Data Measurement Demonstrated on Unmanned
This book considers two popular topics: fault detection and isolation (FDI) and flight data estimation using flush air data sensing (FADS) systems. Literature surveys, comparison tests, simulations and wind tunnel tests are performed. In both cases, a UAV
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Ihab Samy and Da-Wei Gu
Fault Detection and Flight Data Measurement Demonstrated on Unmanned Air Vehicles Using Neural Networks
ABC
Series Advisory Board P. Fleming, P. Kokotovic, A.B. Kurzhanski, H. Kwakernaak, A. Rantzer, J.N. Tsitsiklis
Authors Dr. Ihab Samy
Professor Da-Wei Gu
TRW Ltd. Stratford Road Shirley Solihull B90 4AX UK Email: [email protected]
University of Leicester Department of Engineering University Road Leicester LE1 7RH UK Email: [email protected]
ISBN 978-3-642-24051-5
e-ISBN 978-3-642-24052-2
DOI 10.1007/978-3-642-24052-2 Lecture Notes in Control and Information Sciences
ISSN 0170-8643
Library of Congress Control Number: 2011937286 c 2012 Springer-Verlag London Limited 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 to prosecution under the German Copyright Law. 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. Typeset & Cover Design: Scientific Publishing Services Pvt. Ltd., Chennai, India. Printed on acid-free paper 987654321 springer.com
Dedicated to my parents; Effat and Samy Abou Rayan
Ihab Samy Abou Rayan was born in Alexandria, Egypt in 1983. He received a first class MEng degree in Electrical and Electronics Engineering from the University of Leicester, UK. In 2005 he joined the Control and Instrumentation Group at the University of Leicester, and in 2009 received his PhD title. He has held two post doctoral positions at the University of Leicester and Cranfield University, UK. The latter involved work alongside several international companies including: Boeing, Rolls Royce, BAE Systems and Thales. He is currently a Senior Control Engineer at TRW Ltd, UK.
Preface
This book is essentially the first author’s PhD thesis, which was successfully defended at the University of Leicester in 2009. It explores the feasibility of two technologies in reducing cost and weight of air vehicles. The first is a fault detection and isolation scheme, which uses neural networks to diagnose faults in sensors. The second is a flush air data sensing (FADS) system, which uses pressure orifices on a wing’s leading edge to estimate air data such as; airspeed angle of attack and sideslip. Fault detection and isolation (FDI) can be traced back to the time before the 1940’s when industry did not rely so much on highly mechanised processes and it was sufficient to only fix something when it was truly broken. With
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