Knowledge Commons of Institute of Automation,CAS
Infinite Horizon Self-Learning Optimal Control of Nonaffine Discrete-Time Nonlinear Systems | |
Wei, Qinglai; Liu, Derong; Yang, Xiong | |
发表期刊 | IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS |
2015-04-01 | |
卷号 | 26期号:4页码:866-879 |
文章类型 | Article |
摘要 | In this paper, a novel iterative adaptive dynamic programming (ADP)-based infinite horizon self-learning optimal control algorithm, called generalized policy iteration algorithm, is developed for nonaffine discrete-time (DT) nonlinear systems. Generalized policy iteration algorithm is a general idea of interacting policy and value iteration algorithms of ADP. The developed generalized policy iteration algorithm permits an arbitrary positive semidefinite function to initialize the algorithm, where two iteration indices are used for policy improvement and policy evaluation, respectively. It is the first time that the convergence, admissibility, and optimality properties of the generalized policy iteration algorithm for DT nonlinear systems are analyzed. Neural networks are used to implement the developed algorithm. Finally, numerical examples are presented to illustrate the performance of the developed algorithm. |
关键词 | Adaptive Critic Designs Adaptive Dynamic Programming (Adp) Approximate Dynamic Programming Generalized Policy Iteration Neural Networks (Nns) Neurodynamic Programming Nonlinear Systems Optimal Control Reinforcement Learning |
WOS标题词 | Science & Technology ; Technology |
关键词[WOS] | DYNAMIC-PROGRAMMING ALGORITHM ; OPTIMAL TRACKING CONTROL ; ADAPTIVE OPTIMAL-CONTROL ; ZERO-SUM GAMES ; UNKNOWN DYNAMICS ; CONTROL SCHEME ; POLICY ITERATION ; LINEAR-SYSTEMS ; CRITIC DESIGNS ; HJB SOLUTION |
收录类别 | SCI |
语种 | 英语 |
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:000351835900017 |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/8122 |
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 |
作者单位 | Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China |
第一作者单位 | 中国科学院自动化研究所 |
推荐引用方式 GB/T 7714 | Wei, Qinglai,Liu, Derong,Yang, Xiong. Infinite Horizon Self-Learning Optimal Control of Nonaffine Discrete-Time Nonlinear Systems[J]. IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS,2015,26(4):866-879. |
APA | Wei, Qinglai,Liu, Derong,&Yang, Xiong.(2015).Infinite Horizon Self-Learning Optimal Control of Nonaffine Discrete-Time Nonlinear Systems.IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS,26(4),866-879. |
MLA | Wei, Qinglai,et al."Infinite Horizon Self-Learning Optimal Control of Nonaffine Discrete-Time Nonlinear Systems".IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS 26.4(2015):866-879. |
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Infinite Horizon Sel(2408KB) | 期刊论文 | 出版稿 | 开放获取 | CC BY-NC-SA | 浏览 下载 |
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