Event-Triggered Adaptive Dynamic Programming for Continuous-Time Nonlinear Two-Player Zero-Sum Game

被引：0
|
作者：
Xue, Shan [1 ]
Luo, Biao [2 ]
Liu, Derong [3 ]
Li, Yueheng [1 ]
机构：
[1] Univ Sci & Technol Beijing, Sch Automat & Elect Engn, Beijing 100083, Peoples R China
[2] Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China
[3] Guangdong Univ Technol, Sch Automat, Guangzhou 510006, Peoples R China
来源：
NEURAL INFORMATION PROCESSING (ICONIP 2018), PT VII | 2018年 / 11307卷
基金：
中国国家自然科学基金;
关键词：
Event-triggering control; Adaptive dynamic programming; Two-player zero-sum game; Hamilton-Jacobi-Isaacs equation;
D O I：
10.1007/978-3-030-04239-4_2
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
In this paper, an event-triggered adaptive dynamic programming (ADP) algorithm is developed to solve the two-player zero-sum game problem of continuous-time nonlinear systems. First, a critic neural network is employed to approximate the optimal value function. Then, an event-triggered ADP method is proposed, which guarantees the stability of the closed-loop system. The developed method can save the amount of computation as the control law and disturbance law that update only when the pre-designed triggering condition is violated. Finally, its effectiveness is verified through simulation results.
引用
收藏
页码：15 / 25
页数：11
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