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

文献类型：期刊论文

作者Wei, Qinglai2,5; Zhu, Liao2,5; Song, Ruizhuo1; Zhang, Pinjia4; Liu, Derong3; Xiao, Jun5
刊名IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
出版日期2022-02-01
卷号33期号:2页码:879-892
ISSN号2162-237X
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)
DOI10.1109/TNNLS.2020.3030127
通讯作者Wei, Qinglai(qinglai.wei@ia.ac.cn) ; Xiao, Jun(xiaojun@ucas.ac.cn)
英文摘要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.
WOS关键词SYSTEMS
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]
WOS研究方向Computer Science ; Engineering
语种英语
出版者IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
WOS记录号WOS:000752016400036
资助机构National Natural Science Foundation of China ; National Key Research and Development Program of China
源URL[http://ir.ia.ac.cn/handle/173211/47355]  
专题自动化研究所_复杂系统管理与控制国家重点实验室_智能化团队
通讯作者Wei, Qinglai; Xiao, Jun
作者单位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
4.Tsinghua Univ, Dept Elect Engn, Beijing 100084, Peoples R China
5.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing 100049, Peoples R China
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.

入库方式： OAI收割

来源：自动化研究所

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