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Optimized Multi-Agent Formation Control Based on an Identifier-Actor--Critic Reinforcement Learning Algorithm
Wen, Guoxing1; Chen, C. L. Philip2,3,4; Feng, Jun5,6; Zhou, Ning7,8
发表期刊IEEE TRANSACTIONS ON FUZZY SYSTEMS
ISSN1063-6706
2018-10-01
卷号26期号:5页码:2719-2731
通讯作者Wen, Guoxing(gxwen@live.cn)
摘要The paper proposes an optimized leader-follow er formation control for the multi-agent systems with unknown nonlinear dynamics. Usually, optimal control is designed based on the solution of the Hamilton-Jacobi-Bellman equation, but it is very difficult to solve the equation because of the unknown dynamic and inherent nonlinearity. Specifically, to multi-agent systems, it will become more complicated owing to the state coupling problem in control design. In order to achieve the optimized control, the reinforcement learning algorithm of the identifier-actor-critic architecture is implemented based on fuzzy logic system (FLS) approximators. The identifier is designed for estimating the unknown multi-agent dynamics; the actor and critic FLSs are constructed for executing control behavior and evaluating control performance, respectively. According to Lyapunov stability theory, it is proven that the desired optimizing performance can be arrived. Finally, a simulation example is carried out to further demonstrate the effectiveness of the proposed control approach.
关键词Fuzzy logic systems (FLSs) identifier-actor-critic architecture multi-agent formation optimized formation control reinforcement learning (RL)
DOI10.1109/TFUZZ.2017.2787561
关键词[WOS]FUZZY CONTROL-SYSTEMS ; STABILITY ANALYSIS ; MOBILE ROBOTS ; CONSTRAINTS
收录类别SCI
语种英语
资助项目Doctoral Scientific Research Staring Fund of Binzhou University[2016Y14] ; National Natural Science Foundation of China[61572540] ; National Natural Science Foundation of China[61603094] ; National Natural Science Foundation of China[61603095] ; China Scholarship Council[201707870005] ; Macau Science and Technology Development Fund[019/2015/A] ; Macau Science and Technology Development Fund[024/2015/AMJ] ; Macau Science and Technology Development Fund[079/2017/A2] ; University Macau MYR Grants ; Doctoral Scientific Research Staring Fund of Binzhou University[2016Y14] ; National Natural Science Foundation of China[61572540] ; National Natural Science Foundation of China[61603094] ; National Natural Science Foundation of China[61603095] ; China Scholarship Council[201707870005] ; Macau Science and Technology Development Fund[019/2015/A] ; Macau Science and Technology Development Fund[024/2015/AMJ] ; Macau Science and Technology Development Fund[079/2017/A2] ; University Macau MYR Grants
项目资助者Doctoral Scientific Research Staring Fund of Binzhou University ; National Natural Science Foundation of China ; China Scholarship Council ; Macau Science and Technology Development Fund ; University Macau MYR Grants
WOS研究方向Computer Science ; Engineering
WOS类目Computer Science, Artificial Intelligence ; Engineering, Electrical & Electronic
WOS记录号WOS:000446675400019
出版者IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
引用统计
被引频次:101[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/173211/28106
专题离退休人员
通讯作者Wen, Guoxing
作者单位1.Binzhou Univ, Coll Sci, Binzhou 256600, Peoples R China
2.Univ Macau, Fac Sci & Technol, Dept Comp & Informat Sci, Macau 99999, Peoples R China
3.Dalian Maritime Univ, Dalian 116026, Peoples R China
4.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100080, Peoples R China
5.Nanjing Univ Aeronaut & Astronaut, Coll Comp Sci & Technol, Nanjing 210000, Jiangsu, Peoples R China
6.Binzhou Univ, Dept Informat Engn, Binzhou 256600, Peoples R China
7.Univ Groningen, Fac Sci & Engn, NL-9747 AG Groningen, Netherlands
8.Fujian Agr & Forestry Univ, Coll Comp & Informat Sci, Fuzhou 350002, Fujian, Peoples R China
推荐引用方式
GB/T 7714
Wen, Guoxing,Chen, C. L. Philip,Feng, Jun,et al. Optimized Multi-Agent Formation Control Based on an Identifier-Actor--Critic Reinforcement Learning Algorithm[J]. IEEE TRANSACTIONS ON FUZZY SYSTEMS,2018,26(5):2719-2731.
APA Wen, Guoxing,Chen, C. L. Philip,Feng, Jun,&Zhou, Ning.(2018).Optimized Multi-Agent Formation Control Based on an Identifier-Actor--Critic Reinforcement Learning Algorithm.IEEE TRANSACTIONS ON FUZZY SYSTEMS,26(5),2719-2731.
MLA Wen, Guoxing,et al."Optimized Multi-Agent Formation Control Based on an Identifier-Actor--Critic Reinforcement Learning Algorithm".IEEE TRANSACTIONS ON FUZZY SYSTEMS 26.5(2018):2719-2731.
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