Approximation-error-ADP-based optimal tracking control for chaotic systems with convergence proof

doi:10.1088/1674-1056/22/9/090502

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.

Keywords: chaotic systems approximation error adaptive dynamic programming optimal tracking control

Received: 06 December 2012
Revised: 25 March 2013
Accepted manuscript online:

PACS:

05.45.Gg

(Control of chaos, applications of chaos)

Fund: Project supported by the Open Research Project from SKLMCCS (Grant No. 20120106), the Fundamental Research Funds for the Central Universities of China (Grant No. FRF-TP-13-018A), the Postdoctoral Science Foundation of China (Grant No. 2013M530527), and the National Natural Science Foundation of China (Grant Nos. 61304079, 61125306, and 61034002).

Corresponding Authors: Song Rui-Zhuo
E-mail: ruizhuosong@163.com

Cite this article:

Song Rui-Zhuo (宋睿卓), Xiao Wen-Dong (肖文栋), Sun Chang-Yin (孙长银), Wei Qing-Lai (魏庆来) Approximation-error-ADP-based optimal tracking control for chaotic systems with convergence proof 2013 Chin. Phys. B 22 090502

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Approximation-error-ADP-based optimal tracking control for chaotic systems with convergence proof

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