中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
A novel policy iteration based deterministic Q-learning for discrete-time nonlinear systems

文献类型:期刊论文

作者Wei QingLai1; Liu DeRong2
刊名SCIENCE CHINA-INFORMATION SCIENCES
出版日期2015-12-01
卷号58期号:12
关键词adaptive critic designs adaptive dynamic programming approximate dynamic programming Q-learning policy iteration neural networks nonlinear systems optimal control
英文摘要In this paper, a novel iterative Q-learning algorithm, called "policy iteration based deterministic Q-learning algorithm", is developed to solve the optimal control problems for discrete-time deterministic nonlinear systems. The idea is to use an iterative adaptive dynamic programming (ADP) technique to construct the iterative control law which optimizes the iterative Q function. When the optimal Q function is obtained, the optimal control law can be achieved by directly minimizing the optimal Q function, where the mathematical model of the system is not necessary. Convergence property is analyzed to show that the iterative Q function is monotonically non-increasing and converges to the solution of the optimality equation. It is also proven that any of the iterative control laws is a stable control law. Neural networks are employed to implement the policy iteration based deterministic Q-learning algorithm, by approximating the iterative Q function and the iterative control law, respectively. Finally, two simulation examples are presented to illustrate the performance of the developed algorithm.
WOS标题词Science & Technology ; Technology
类目[WOS]Computer Science, Information Systems
研究领域[WOS]Computer Science
关键词[WOS]OPTIMAL TRACKING CONTROL ; DYNAMIC-PROGRAMMING ALGORITHM ; CONTROL SCHEME ; APPROXIMATION ERRORS ; REINFORCEMENT
收录类别SCI
语种英语
WOS记录号WOS:000368790400015
源URL[http://ir.ia.ac.cn/handle/173211/10670]  
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1.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China
2.Univ Sci & Technol Beijing, Sch Automat & Elect Engn, Beijing 100083, Peoples R China
推荐引用方式
GB/T 7714
Wei QingLai,Liu DeRong. A novel policy iteration based deterministic Q-learning for discrete-time nonlinear systems[J]. SCIENCE CHINA-INFORMATION SCIENCES,2015,58(12).
APA Wei QingLai,&Liu DeRong.(2015).A novel policy iteration based deterministic Q-learning for discrete-time nonlinear systems.SCIENCE CHINA-INFORMATION SCIENCES,58(12).
MLA Wei QingLai,et al."A novel policy iteration based deterministic Q-learning for discrete-time nonlinear systems".SCIENCE CHINA-INFORMATION SCIENCES 58.12(2015).

入库方式: OAI收割

来源:自动化研究所

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