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基于自适应动态规划的一类带有时滞的离散时间非线性系统的最优控制策略
引用本文:魏庆来,张化光,刘德荣,赵琰.基于自适应动态规划的一类带有时滞的离散时间非线性系统的最优控制策略[J].自动化学报,2010,36(1):121-129.
作者姓名:魏庆来  张化光  刘德荣  赵琰
作者单位:1.中国科学院自动化研究所 北京 100190
基金项目:Supported by National High Technology Research and Development Program of China (863 Program) (2006AA04Z183);;National Natural Science Foundation of China (60621001, 60534010, 60572070,60774048, 60728307);;the Program for Changjiang Scholars and Innovative Research Groups of China (60728307, 4031002)
摘    要:针对一类状态和控制变量均带有时滞的非线性系统的带有二次性能指标函数最优控制问题, 本文提出了一种基于新的迭代自适应动态规划算法的最优控制方案. 通过引进时滞矩阵函数, 应用动态规划理论, 本文获得了最优控制的显式表达式, 然后通过自适应评判技术获得最优控制量. 本文给出了收敛性证明以保证性能指标函数收敛到最优. 为了实现所提出的算法, 本文采用神经网络近似性能指标函数、计算最优控制策略、求解时滞矩阵函数、以及给非线性系统建模. 最后本文给出了两个仿真例子说明所提出的最优策略的有效性.

关 键 词:自适应动态规划(ADP)    近似动态规划    时滞    最优控制    非线性系统    神经网络
收稿时间:2008-9-5
修稿时间:2009-3-3

An Optimal Control Scheme for a Class of Discrete-time Nonlinear Systems with Time Delays Using Adaptive Dynamic Programming
WEI Qing-Lai ZHANG Hua-Guang LIU De-Rong ZHAO Yan.Key Laboratory of Complex Systems , Intelligence Science.An Optimal Control Scheme for a Class of Discrete-time Nonlinear Systems with Time Delays Using Adaptive Dynamic Programming[J].Acta Automatica Sinica,2010,36(1):121-129.
Authors:WEI Qing-Lai ZHANG Hua-Guang LIU De-Rong ZHAO YanKey Laboratory of Complex Systems  Intelligence Science
Affiliation:1.Key Laboratory of Complex Systems and Intelligence Science, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, P.R. China;2.School of Information Science and Engineering, Northeastern University, Shenyang 110004, P.R. China;3.Department of Automatic Control Engineering, Shenyang Institute of Engineering, Shenyang 110136, P.R. China
Abstract:In this paper, an optimal control scheme for a class of nonlinear systems with time delays in both state and control variables with respect to a quadratic performance index function is proposed using a new iterative adaptive dynamic programming (ADP) algorithm. By introducing a delay matrix function, the explicit expression of the optimal control is obtained using the dynamic programming theory and the optimal control can iteratively be obtained using the adaptive critic technique. Convergence analysis is presented to prove that the performance index function can reach the optimum by the proposed method. Neural networks are used to approximate the performance index function, compute the optimal control policy, solve delay matrix function, and model the nonlinear system, respectively, for facilitating the implementation of the iterative ADP algorithm. Two examples are given to demonstrate the validity of the proposed optimal control scheme.
Keywords:Adaptive dynamic programming (ADP)  approximate dynamic programming  time delay  optimal control  nonlinear system  neural networks
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