Adaptive tracking control for a class of continuous-time uncertain nonlinear systems using the approximate solution of HJB equation
文献类型：期刊论文
| 作者 | Mu, Chaoxu1,2,3; Sun, Changyin2; Wang, Ding3 ; Song, Aiguo4
|
| 刊名 | NEUROCOMPUTING
 |
| 出版日期 | 2017-10-18 |
| 卷号 | 260页码:432-442 |
| 关键词 | Adaptive Tracking Control Hamilton-jacobi-bellman (Hjb) Equation Adaptive Dynamic Programming (Adp) Neural Networks Uncertainties |
| DOI | 10.1016/j.neucom.2017.04.043 |
| 文献子类 | Article |
| 英文摘要 | In this paper, an adaptive tracking control scheme is designed for a class of continuous-time uncertain nonlinear systems based on the approximate solution of the Hamilton-Jacobi-Bellman (HJB) equation. Considering matched uncertainties, the tracking control of the continuous-time uncertain nonlinear system can be transformed to the optimal tracking control of the associated nominal system. By building the nominal error system and modifying its cost function, the solution of the relevant FIJB equation can be contributed to the adaptive tracking control of the continuous-time uncertain nonlinear system. In view of the complexity on solving the HJB equation, its approximate solution is pursued by the policy iteration algorithm under the adaptive dynamic programming (ADP) framework, where a critic neural network is constructed to approximate the optimal cost function, and an action network is used to directly calculate the approximate optimal control law, which constitutes the tracking control law for the original uncertain system together with the steady control law. The weight convergence of the critic network and the stability of the closed-loop system are provided as the theoretical guarantee based on the Lyapunov theory. Two simulation examples are studied to verify the theoretical results and the effectiveness of the proposed tracking control scheme. (C) 2017 Elsevier B.V. All rights reserved. |
| WOS关键词 | FEEDBACK-CONTROL ; DEAD-ZONE ; REINFORCEMENT ; INPUT ; DESIGN |
| WOS研究方向 | Computer Science |
| 语种 | 英语 |
| WOS记录号 | WOS:000405536900044 |
| 资助机构 | National Natural Science Foundation of China(U1501251 ; China Postdoctoral Science Foundation(2014M561559) ; Tianjin Natural Science Foundation(14JCQNJC05400) ; Beijing Natural Science Foundation(4162065) ; 61533008 ; 61533017 ; 61520106009) |
| 源URL | [http://ir.ia.ac.cn/handle/173211/15278]  |
| 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.Tianjin Univ, Sch Elect & Informat Engn, Tianjin Key Lab Proc Measurement & Control, Tianjin 300072, Peoples R China 2.Southeast Univ, Sch Automat, Nanjing 210096, Jiangsu, Peoples R China 3.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China 4.Southeast Univ, Sch Instrument Sci & Engn, Nanjing 210096, Jiangsu, Peoples R China |
| 推荐引用方式 GB/T 7714 | Mu, Chaoxu,Sun, Changyin,Wang, Ding,et al. Adaptive tracking control for a class of continuous-time uncertain nonlinear systems using the approximate solution of HJB equation[J]. NEUROCOMPUTING,2017,260:432-442. |
| APA | Mu, Chaoxu,Sun, Changyin,Wang, Ding,&Song, Aiguo.(2017).Adaptive tracking control for a class of continuous-time uncertain nonlinear systems using the approximate solution of HJB equation.NEUROCOMPUTING,260,432-442. |
| MLA | Mu, Chaoxu,et al."Adaptive tracking control for a class of continuous-time uncertain nonlinear systems using the approximate solution of HJB equation".NEUROCOMPUTING 260(2017):432-442. |
入库方式： OAI收割
来源：自动化研究所
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