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Iterative Adaptive Dynamic Programming for Solving Unknown Nonlinear Zero-Sum Game Based on Online Data
Zhu, Yuanheng1; Zhao, Dongbin1,2; Li, Xiangjun3
Source PublicationIEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
2017-03-01
Volume28Issue:3Pages:714-725
SubtypeArticle
AbstractH-infinity control is a powerful method to solve the disturbance attenuation problems that occur in some control systems. The design of such controllers relies on solving the zero-sum game (ZSG). But in practical applications, the exact dynamics is mostly unknown. Identification of dynamics also produces errors that are detrimental to the control performance. To overcome this problem, an iterative adaptive dynamic programming algorithm is proposed in this paper to solve the continuous-time, unknown nonlinear ZSG with only online data. A model-free approach to the Hamilton-Jacobi-Isaacs equation is developed based on the policy iteration method. Control and disturbance policies and value are approximated by neural networks (NNs) under the critic-actor-disturber structure. The NN weights are solved by the least-squares method. According to the theoretical analysis, our algorithm is equivalent to a Gauss-Newton method solving an optimization problem, and it converges uniformly to the optimal solution. The online data can also be used repeatedly, which is highly efficient. Simulation results demonstrate its feasibility to solve the unknown nonlinear ZSG. When compared with other algorithms, it saves a significant amount of online measurement time.
KeywordAdaptive Dynamic Programming (Adp) H-infinity Control Policy Iteration (Pi) Zero-sum Game (Zsg)
WOS HeadingsScience & Technology ; Technology
DOI10.1109/TNNLS.2016.2561300
WOS KeywordH-INFINITY CONTROL ; STATE-FEEDBACK CONTROL ; DISCRETE-TIME-SYSTEMS ; POLICY UPDATE ALGORITHM ; LEARNING ALGORITHM ; CRITIC DESIGNS ; CONTROL LAWS ; APPROXIMATION ; EQUATIONS
Indexed BySCI
Language英语
Funding OrganizationNational Natural Science Foundation of China(61273136 ; Beijing Nova Program(Z141101001814094) ; Science and Technology Foundation of State Grid Corporation of China(DG71-14-032) ; 61573353 ; 61533017)
WOS Research AreaComputer Science ; Engineering
WOS SubjectComputer Science, Artificial Intelligence ; Computer Science, Hardware & Architecture ; Computer Science, Theory & Methods ; Engineering, Electrical & Electronic
WOS IDWOS:000395980500020
Citation statistics
Cited Times:25[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/14403
Collection复杂系统管理与控制国家重点实验室_深度强化学习
Affiliation1.Chinese Acad Sci, State Key Lab Management & Control Complex Syst, Inst Automat, Beijing 100190, Peoples R China
2.Univ Chinese Acad Sci, Beijing 100049, Peoples R China
3.China Elect Power Res Inst, State Key Lab Control & Operat Renewable Energy &, Beijing 100192, Peoples R China
Recommended Citation
GB/T 7714
Zhu, Yuanheng,Zhao, Dongbin,Li, Xiangjun. Iterative Adaptive Dynamic Programming for Solving Unknown Nonlinear Zero-Sum Game Based on Online Data[J]. IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS,2017,28(3):714-725.
APA Zhu, Yuanheng,Zhao, Dongbin,&Li, Xiangjun.(2017).Iterative Adaptive Dynamic Programming for Solving Unknown Nonlinear Zero-Sum Game Based on Online Data.IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS,28(3),714-725.
MLA Zhu, Yuanheng,et al."Iterative Adaptive Dynamic Programming for Solving Unknown Nonlinear Zero-Sum Game Based on Online Data".IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS 28.3(2017):714-725.
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