Modeling and Identification of Linear Parameter-Varying Systems
Through the past 20 years, the framework of Linear Parameter-Varying (LPV) systems has become a promising system theoretical approach to handle the control of mildly nonlinear and especially position dependent systems which are common in mechatronic appli
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Roland Tóth
Modeling and Identification of Linear Parameter-Varying Systems
ABC
Series Advisory Board P. Fleming, P. Kokotovic, A.B. Kurzhanski, H. Kwakernaak, A. Rantzer, J.N. Tsitsiklis
Author Dr. Roland Tóth Delft University of Technology Faculty of Mechanical, Maritime and Materials Engineering Delft Center for Systems and Control Mekelweg 2 2628 CD, Delft The Netherlands Co-Editors Dr. Peter S.C. Heuberger Delft University of Technology Faculty of Mechanical, Maritime and Materials Engineering Delft Center for Systems and Control Mekelweg 2 2628 CD, Delft The Netherlands
Prof. Dr. Paul M.J. Van den Hof Delft University of Technology Faculty of Mechanical, Maritime and Materials Engineering Delft Center for Systems and Control Mekelweg 2 2628 CD, Delft The Netherlands
ISBN 978-3-642-13811-9
e-ISBN 978-3-642-13812-6
DOI 10.1007/978-3-642-13812-6 Lecture Notes in Control and Information Sciences
ISSN 0170-8643
Library of Congress Control Number: 2010928272 c
2010 Springer-Verlag Berlin Heidelberg
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I dedicate this book to my beloved wife Andrea, my “great” son S´ andor and my little daughter Lujza.
Preface
Through the past 20 years, the framework of Linear Parameter-Varying (LPV) systems has become a promising system theoretical approach to handle the control of mildly nonlinear and especially position dependent systems which are common in mechatronic applications and in the process industry. The birth of this system class was initiated by the need of engineers to achieve better performance for nonlinear and time-varying dynamics, common in many industrial applications, than what the classical framework of Linear Time-Invariant (LTI) control can provide. However, it was also a primary goal to preserve simplicity and “re-use” the powerful LTI results by extending them to the LPV case. The progress continued according to this philosophy and LPV control has become a well established field with many promising applications. Unfortunately, modeling of LPV systems, especially based on measured data (which is called system identification) has seen
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