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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