Knowledge Commons of Institute of Automation，CAS
| A neural-network-based online optimal control approach for nonlinear robust decentralized stabilization | |
Wang, Ding ; Liu, Derong; Li, Hongliang; Ma, Hongwen; Li, Chao
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| 发表期刊 | SOFT COMPUTING
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| 2016-02-01 | |
| 卷号 | 20期号:2页码:707-716 |
| 文章类型 | Article |
| 摘要 | In this paper, the robust decentralized stabilization of continuous-time uncertain nonlinear systems with multi control stations is developed using a neural network based online optimal control approach. The novelty lies in that the well-known adaptive dynamic programming method is extended to deal with the nonlinear feedback control problem under uncertain and large-scale environment. Through introducing an appropriate bounded function and defining a modified cost function, it can be observed that the decentralized optimal controller of the nominal system can achieve robust decentralized stabilization of original uncertain system. Then, a critic neural network is constructed for solving the modified Hamilton-Jacobi-Bellman equation corresponding to the nominal system in an online fashion. The weights of the critic network are tuned based on the standard steepest descent algorithm with an additional term provided to guarantee the boundedness of system states. The stability analysis of the closed-loop system is carried out via the Lyapunov approach. At last, two simulation examples are given to verify the effectiveness of the present control approach. |
| 关键词 | Adaptive Dynamic Programming Approximate Dynamic Programming Neural Networks Online Optimal Control Robust Decentralized Stabilization Uncertain Nonlinear Systems |
| WOS标题词 | Science & Technology ; Technology |
| DOI | 10.1007/s00500-014-1534-z |
| 关键词[WOS] | DYNAMIC-PROGRAMMING ALGORITHM ; DISCRETE-TIME-SYSTEMS ; TRACKING CONTROL ; FEEDBACK-CONTROL ; POLICY UPDATE ; HJB SOLUTION ; DESIGN ; CONSTRAINTS ; EQUATION |
| 收录类别 | SCI |
| 语种 | 英语 |
| 项目资助者 | National Natural Science Foundation of China(61034002 ; Beijing Natural Science Foundation(4132078) ; Early Career Development Award of SKLMCCS ; 61233001 ; 61273140 ; 61304086 ; 61374105) |
| WOS研究方向 | Computer Science |
| WOS类目 | Computer Science, Artificial Intelligence ; Computer Science, Interdisciplinary Applications |
| WOS记录号 | WOS:000372297200021 |
| 引用统计 | |
| 文献类型 | 期刊论文 |
| 条目标识符 | http://ir.ia.ac.cn/handle/173211/11378 |
| 专题 | 多模态人工智能系统全国重点实验室_复杂系统智能机理与平行控制团队 |
| 作者单位 | Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China |
| 第一作者单位 | 中国科学院自动化研究所 |
| 推荐引用方式 GB/T 7714 | Wang, Ding,Liu, Derong,Li, Hongliang,et al. A neural-network-based online optimal control approach for nonlinear robust decentralized stabilization[J]. SOFT COMPUTING,2016,20(2):707-716. |
| APA | Wang, Ding,Liu, Derong,Li, Hongliang,Ma, Hongwen,&Li, Chao.(2016).A neural-network-based online optimal control approach for nonlinear robust decentralized stabilization.SOFT COMPUTING,20(2),707-716. |
| MLA | Wang, Ding,et al."A neural-network-based online optimal control approach for nonlinear robust decentralized stabilization".SOFT COMPUTING 20.2(2016):707-716. |
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