Model-Free Adaptive Optimal Control for Unknown Nonlinear Multiplayer Nonzero-Sum Game

doi:10.1109/TNNLS.2020.3030127

CASIA OpenIR > 多模态人工智能系统全国重点实验室 > 复杂系统智能机理与平行控制团队

	Model-Free Adaptive Optimal Control for Unknown Nonlinear Multiplayer Nonzero-Sum Game
	Wei, Qinglai1,2 ; Zhu, Liao1,2 ; Song, Ruizhuo 3; Zhang, Pinjia 4; Liu, Derong 5; Xiao, Jun 2
发表期刊	IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
ISSN	2162-237X
	2022-02-01
卷号	33 期号:2 页码:879-892
通讯作者	Wei, Qinglai(qinglai.wei@ia.ac.cn) ; Xiao, Jun(xiaojun@ucas.ac.cn)
摘要	In this article, an online adaptive optimal control algorithm based on adaptive dynamic programming is developed to solve the multiplayer nonzero-sum game (MP-NZSG) for discrete-time unknown nonlinear systems. First, a model-free coupled globalized dual-heuristic dynamic programming (GDHP) structure is designed to solve the MP-NZSG problem, in which there is no model network or identifier. Second, in order to relax the requirement of systems dynamics, an online adaptive learning algorithm is developed to solve the Hamilton-Jacobi equation using the system states of two adjacent time steps. Third, a series of critic networks and action networks are used to approximate value functions and optimal policies for all players. All the neural network (NN) weights are updated online based on real-time system states. Fourth, the uniformly ultimate boundedness analysis of the NN approximation errors is proved based on the Lyapunov approach. Finally, simulation results are given to demonstrate the effectiveness of the developed scheme.
关键词	Heuristic algorithms Nonlinear systems Optimal control Mathematical model Dynamic programming Games Adaptive systems Adaptive dynamic programming (ADP) globalized dual-heuristic dynamic programming (GDHP) multiplayer nonzero-sum game (MP-NZSG) neural network (NN)
DOI	10.1109/TNNLS.2020.3030127
关键词[WOS]	SYSTEMS
收录类别	SCI
语种	英语
资助项目	National Natural Science Foundation of China[61722312] ; National Natural Science Foundation of China[62073321] ; National Natural Science Foundation of China[61673054] ; National Natural Science Foundation of China[61533017] ; National Key Research and Development Program of China[2018YFB1702300]
项目资助者	National Natural Science Foundation of China ; National Key Research and Development Program of China
WOS研究方向	Computer Science ; Engineering
WOS类目	Computer Science, Artificial Intelligence ; Computer Science, Hardware & Architecture ; Computer Science, Theory & Methods ; Engineering, Electrical & Electronic
WOS记录号	WOS:000752016400036
出版者	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
七大方向——子方向分类	智能控制
引用统计	被引频次：44[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.ia.ac.cn/handle/173211/47356
专题	多模态人工智能系统全国重点实验室_复杂系统智能机理与平行控制团队
通讯作者	Wei, Qinglai; Xiao, Jun
作者单位	1.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China 2.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing 100049, Peoples R China 3.Univ Sci & Technol Beijing, Sch Automat & Elect Engn, Beijing 100083, Peoples R China 4.Tsinghua Univ, Dept Elect Engn, Beijing 100084, Peoples R China 5.Guangdong Univ Technol, Sch Automat, Guangzhou 510006, Peoples R China
第一作者单位	中国科学院自动化研究所
通讯作者单位	中国科学院自动化研究所
推荐引用方式 GB/T 7714	Wei, Qinglai,Zhu, Liao,Song, Ruizhuo,et al. Model-Free Adaptive Optimal Control for Unknown Nonlinear Multiplayer Nonzero-Sum Game[J]. IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS,2022,33(2):879-892.
APA	Wei, Qinglai,Zhu, Liao,Song, Ruizhuo,Zhang, Pinjia,Liu, Derong,&Xiao, Jun.(2022).Model-Free Adaptive Optimal Control for Unknown Nonlinear Multiplayer Nonzero-Sum Game.IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS,33(2),879-892.
MLA	Wei, Qinglai,et al."Model-Free Adaptive Optimal Control for Unknown Nonlinear Multiplayer Nonzero-Sum Game".IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS 33.2(2022):879-892.