Approximation-error-ADP-based optimal tracking control for chaotic systems with convergence proof |
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Authors: | Song Rui-Zhuo Xiao Wen-Dong Sun Chang-Yin and Wei Qing-Lai |
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Institution: | [1]School of Automation and Electrical Engineering, University of Science and Technology Beijing, Beijing 100083, China [2]The State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China |
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Abstract: | In this paper, an optimal tracking control scheme is proposed for a class of discrete-time chaotic systems using the approximation-error-based adaptive dynamic programming (ADP) algorithm. Via the system transformation, the optimal tracking problem is transformed into an optimal regulation problem, and then the novel optimal tracking control method is proposed. It is shown that for the iterative ADP algorithm with finite approximation error, the iterative performance index functions can converge to a finite neighborhood of the greatest lower bound of all performance index functions under some convergence conditions. Two examples are given to demonstrate the validity of the proposed optimal tracking control scheme for chaotic systems. |
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Keywords: | chaotic systems approximation error adaptive dynamic programming optimal tracking control |
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