Infinite Horizon Self-Learning Optimal Control of Nonaffine Discrete-Time Nonlinear Systems
文献类型：期刊论文
| 作者 | Wei, Qinglai ; Liu, Derong; Yang, Xiong
|
| 刊名 | IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
 |
| 出版日期 | 2015-04-01 |
| 卷号 | 26期号:4页码:866-879 |
| 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 |
| 英文摘要 | 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. |
| WOS标题词 | Science & Technology ; Technology |
| 类目[WOS] | Computer Science, Artificial Intelligence ; Computer Science, Hardware & Architecture ; Computer Science, Theory & Methods ; Engineering, Electrical & Electronic |
| 研究领域[WOS] | Computer Science ; Engineering |
| 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记录号 | WOS:000351835900017 |
| 公开日期 | 2015-09-22 |
| 源URL | [http://ir.ia.ac.cn/handle/173211/8122]  |
| 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 |
| 作者单位 | Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China |
| 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. |
入库方式： OAI收割
来源：自动化研究所
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