Modelling and Control of Dynamic Systems Using Gaussian Process Models
This monograph opens up new horizons for engineers and researchers in academia and in industry dealing with or interested in new developments in the field of system identification and control. It emphasizes guidelines for working solutions and practical a
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Juš Kocijan
Modelling and Control of Dynamic Systems Using Gaussian Process Models
Advances in Industrial Control Series editors Michael J. Grimble, Glasgow, UK Michael A. Johnson, Kidlington, UK
More information about this series at http://www.springer.com/series/1412
Juš Kocijan
Modelling and Control of Dynamic Systems Using Gaussian Process Models
123
Juš Kocijan Department of Systems and Control Jožef Stefan Institute Ljubljana Slovenia and Centre for Systems and Information Technologies University of Nova Gorica Nova Gorica Slovenia
Additional material to this book can be downloaded from http://extras.springer.com. ISSN 1430-9491 Advances in Industrial Control ISBN 978-3-319-21020-9 DOI 10.1007/978-3-319-21021-6
ISSN 2193-1577
(electronic)
ISBN 978-3-319-21021-6
(eBook)
Library of Congress Control Number: 2015954342 Springer Cham Heidelberg New York Dordrecht London © Springer International Publishing Switzerland 2016 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, express or implied, with respect to the material contained herein or for any errors or omissions that may have been made. Printed on acid-free paper Springer International Publishing AG Switzerland is part of Springer Science+Business Media (www.springer.com)
Series Editors’ Foreword
The series Advances in Industrial Control aims to report and encourage technology transfer in control engineering. The rapid development of control technology has an impact on all areas of the control discipline. New theory, new controllers, actuators, sensors, new industrial processes, computer methods, new applications, new philosophies…, new challenges. Much of this development work resides in industrial reports, feasibility study papers and the reports of advanced collaborative projects. The series offers an opportunity for researchers to present an extended exposition of such new work in all aspects of industrial control for wider and rapid dissemination. For classical low-level industrial PID controllers a widespread tuning paradigm is based on nonparametric tuning methods pioneered by Ziegler and Nichols in the 1940s. The tra
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