Self-Learning Optimal Control of Nonlinear Systems Adaptive Dynamic
This book presents a class of novel, self-learning, optimal control schemes based on adaptive dynamic programming techniques, which quantitatively obtain the optimal control schemes of the systems. It analyzes the properties identified by the programming
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Qinglai Wei Ruizhuo Song Benkai Li Xiaofeng Lin
Self-Learning Optimal Control of Nonlinear Systems Adaptive Dynamic Programming Approach
Studies in Systems, Decision and Control Volume 103
Series editor Janusz Kacprzyk, Polish Academy of Sciences, Warsaw, Poland e-mail: [email protected]
About this Series The series “Studies in Systems, Decision and Control” (SSDC) covers both new developments and advances, as well as the state of the art, in the various areas of broadly perceived systems, decision making and control- quickly, up to date and with a high quality. The intent is to cover the theory, applications, and perspectives on the state of the art and future developments relevant to systems, decision making, control, complex processes and related areas, as embedded in the fields of engineering, computer science, physics, economics, social and life sciences, as well as the paradigms and methodologies behind them. The series contains monographs, textbooks, lecture notes and edited volumes in systems, decision making and control spanning the areas of Cyber-Physical Systems, Autonomous Systems, Sensor Networks, Control Systems, Energy Systems, Automotive Systems, Biological Systems, Vehicular Networking and Connected Vehicles, Aerospace Systems, Automation, Manufacturing, Smart Grids, Nonlinear Systems, Power Systems, Robotics, Social Systems, Economic Systems and other. Of particular value to both the contributors and the readership are the short publication timeframe and the world-wide distribution and exposure which enable both a wide and rapid dissemination of research output.
More information about this series at http://www.springer.com/series/13304
Qinglai Wei Ruizhuo Song Benkai Li Xiaofeng Lin •
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Self-Learning Optimal Control of Nonlinear Systems Adaptive Dynamic Programming Approach
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Qinglai Wei Institute of Automation Chinese Academy of Sciences Beijing China
Benkai Li Institute of Automation Chinese Academy of Sciences Beijing China
Ruizhuo Song University of Science and Technology Beijing Beijing China
Xiaofeng Lin Guangxi University Guangxi China
ISSN 2198-4182 ISSN 2198-4190 (electronic) Studies in Systems, Decision and Control ISBN 978-981-10-4079-5 ISBN 978-981-10-4080-1 (eBook) DOI 10.1007/978-981-10-4080-1 Jointly published with Science Press, Beijing, China ISBN: 978-7-03-052060-9, Science Press, Beijing, China Not for sale outside the Mainland of China (Not for sale in Hong Kong SAR, Macau SAR, and Taiwan, and all countries, except the Mainland of China) Library of Congress Control Number: 2017934060 © Science Press, Beijing and Springer Nature Singapore Pte Ltd. 2018 This work is subject to copyright. All rights are reserved by the Publishers, 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 dissi
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