Local Policy Iteration Adaptive Dynamic Programming for Discrete-Time Nonlinear Systems

被引：0
|
作者：
Wei, Qinglai [1 ]
Xu, Yancai [1 ]
Lin, Qiao [1 ]
Liu, Derong [2 ]
Song, Ruizhuo [2 ]
机构：
[1] Univ Chinese Acad Sci, Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China
[2] Univ Sci & Technol Beijing, Sch Automat & Elect Engn, Beijing 100083, Peoples R China
来源：
ADVANCES IN NEURAL NETWORKS, PT II | 2017年 / 10262卷
基金：
中国国家自然科学基金;
关键词：
Nonlinear systems; Approximate dynamic programming; Local policy iteration; Optimal control; Discrete time; DESIGN; GAMES;
D O I：
10.1007/978-3-319-59081-3_18
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Adaptive dynamic programming is a hot research topic nowadays. Therefore, the paper concerns a new local policy adaptive iterative dynamic programming (ADP) algorithm. Moreover, this algorithm is designed for the discrete-time nonlinear systems, which are used to solve problems concerning infinite horizon optimal control. The new local policy iteration ADP algorithm has the characteristics of updating the iterative control law and value function within one subset of the state space. Morevover, detailed iteration process of the local policy iteration is presented thereafter. The simulation example is listed to show the good performance of the newly developed algorithm.
引用
收藏
页码：148 / 153
页数：6
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