Optimal control for a class of nonlinear systems with state delay based on Adaptive Dynamic Programming with ε-error bound

被引：0
|
作者：
Lin, Xiaofeng [1 ]
Cao, Nuyun [1 ]
Lin, Yuzhang [2 ]
机构：
[1] Guangxi Univ, Sch Elect Engn, Nanning 530004, Peoples R China
[2] Tsinghua Univ, Dept Elect Engn, Beijing, Peoples R China
来源：
PROCEEDINGS OF THE 2013 IEEE SYMPOSIUM ON ADAPTIVE DYNAMIC PROGRAMMING AND REINFORCEMENT LEARNING (ADPRL) | 2013年
基金：
中国国家自然科学基金;
关键词：
Adaptive Dynamic Programming; state delay; epsilon-optimal control; finite time; nonlinear systems; LINEAR-SYSTEMS; TIME;
D O I：
暂无
中图分类号：
TP301 [理论、方法];
学科分类号：
081202 ;
摘要：
In this paper, a finite-horizon epsilon-optimal control for a class of nonlinear systems with state delay is proposed by Adaptive Dynamic Programming (ADP) algorithm. First of all, the performance index function is defined and the Hamilton-Jacobi-Bellman (HJB) equation is obtained for the problem, the convergence of the iterative algorithm is also presented. Then, ADP algorithm for finite-horizon optimal control is introduced with an epsilon-error bound so as to get the epsilon-optimal control, and BP neural network is used to implement ADP algorithm. At last, an example is given to demonstrate the effectiveness of the proposed algorithm.
引用
收藏
页码：177 / 182
页数：6
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