Neural-network-based adaptive optimal tracking control scheme for discrete-time nonlinear systems with approximation errors
文献类型：期刊论文
| 作者 | Wei, Qinglai ; Liu, Derong; Qinglai Wei
|
| 刊名 | NEUROCOMPUTING
 |
| 出版日期 | 2015-02-03 |
| 卷号 | 149页码:106-115 |
| 关键词 | Adaptive dynamic programming Adaptive critic designs Approximate dynamic programming Value iteration Approximation errors Optimal tracking control |
| 英文摘要 | In this paper, a new infinite horizon neural-network-based adaptive optimal tracking control scheme for discrete-time nonlinear systems is developed. The idea is to use iterative adaptive dynamic programming (ADP) algorithm to obtain the iterative tracking control law which makes the iterative performance index function reach the optimum. When the iterative tracking control law and iterative performance index function in each iteration cannot be accurately obtained, the convergence criteria of the iterative ADP algorithm are established according to the properties with finite approximation errors. If the convergence conditions are satisfied, it shows that the iterative performance index functions can converge to a finite neighborhood of the lowest bound of all performance index functions. Properties of the finite approximation errors for the iterative ADP algorithm are also analyzed. Neural networks are used to approximate the performance index function and compute the optimal control policy, respectively, for facilitating the implementation of the iterative ADP algorithm. Convergence properties of the neural network weights are proven. Finally, simulation results are given to illustrate the performance of the developed method. (C) 2014 Elsevier B.V. All rights reserved. |
| WOS标题词 | Science & Technology ; Technology |
| 类目[WOS] | Computer Science, Artificial Intelligence |
| 研究领域[WOS] | Computer Science |
| 关键词[WOS] | DYNAMIC-PROGRAMMING ALGORITHM ; ONLINE LEARNING CONTROL ; CRITIC DESIGNS ; REINFORCEMENT ; CONVERGENCE ; ITERATION ; PROOF |
| 收录类别 | SCI |
| 语种 | 英语 |
| WOS记录号 | WOS:000360028800015 |
| 公开日期 | 2015-12-24 |
| 源URL | [http://ir.ia.ac.cn/handle/173211/8958]  |
| 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 |
| 通讯作者 | Qinglai Wei |
| 作者单位 | Chinese Acad Sci, State Key Lab Management & Control Complex Syst, Inst Automat, Beijing 100190, Peoples R China |
| 推荐引用方式 GB/T 7714 | Wei, Qinglai,Liu, Derong,Qinglai Wei. Neural-network-based adaptive optimal tracking control scheme for discrete-time nonlinear systems with approximation errors[J]. NEUROCOMPUTING,2015,149:106-115. |
| APA | Wei, Qinglai,Liu, Derong,&Qinglai Wei.(2015).Neural-network-based adaptive optimal tracking control scheme for discrete-time nonlinear systems with approximation errors.NEUROCOMPUTING,149,106-115. |
| MLA | Wei, Qinglai,et al."Neural-network-based adaptive optimal tracking control scheme for discrete-time nonlinear systems with approximation errors".NEUROCOMPUTING 149(2015):106-115. |
入库方式： OAI收割
来源：自动化研究所
浏览0
下载0
收藏0
其他版本
除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。