Reinforcement-Learning-Based Robust Controller Design for Continuous-Time Uncertain Nonlinear Systems Subject to Input Constraints
文献类型：期刊论文
| 作者 | Liu, Derong; Yang, Xiong ; Wang, Ding; Wei, Qinglai
|
| 刊名 | IEEE TRANSACTIONS ON CYBERNETICS
 |
| 出版日期 | 2015-07-01 |
| 卷号 | 45期号:7页码:1372-1385 |
| 关键词 | Approximate dynamic programming (ADP) neural networks (NNs) neuro-dynamic programming nonlinear systems optimal control reinforcement learning (RL) robust control |
| 英文摘要 | The design of stabilizing controller for uncertain nonlinear systems with control constraints is a challenging problem. The constrained-input coupled with the inability to identify accurately the uncertainties motivates the design of stabilizing controller based on reinforcement-learning (RL) methods. In this paper, a novel RL-based robust adaptive control algorithm is developed for a class of continuous-time uncertain nonlinear systems subject to input constraints. The robust control problem is converted to the constrained optimal control problem with appropriately selecting value functions for the nominal system. Distinct from typical action-critic dual networks employed in RL, only one critic neural network (NN) is constructed to derive the approximate optimal control. Meanwhile, unlike initial stabilizing control often indispensable in RL, there is no special requirement imposed on the initial control. By utilizing Lyapunov's direct method, the closed-loop optimal control system and the estimated weights of the critic NN are proved to be uniformly ultimately bounded. In addition, the derived approximate optimal control is verified to guarantee the uncertain nonlinear system to be stable in the sense of uniform ultimate boundedness. Two simulation examples are provided to illustrate the effectiveness and applicability of the present approach. |
| WOS标题词 | Science & Technology ; Technology |
| 类目[WOS] | Computer Science, Artificial Intelligence ; Computer Science, Cybernetics |
| 研究领域[WOS] | Computer Science |
| 关键词[WOS] | DYNAMIC-PROGRAMMING ALGORITHM ; ADAPTIVE OPTIMAL-CONTROL ; TRACKING CONTROL ; ARCHITECTURE ; NETWORKS |
| 收录类别 | SCI |
| 语种 | 英语 |
| WOS记录号 | WOS:000356386300013 |
| 公开日期 | 2015-09-22 |
| 源URL | [http://ir.ia.ac.cn/handle/173211/7917]  |
| 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 | Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China |
| 推荐引用方式 GB/T 7714 | Liu, Derong,Yang, Xiong,Wang, Ding,et al. Reinforcement-Learning-Based Robust Controller Design for Continuous-Time Uncertain Nonlinear Systems Subject to Input Constraints[J]. IEEE TRANSACTIONS ON CYBERNETICS,2015,45(7):1372-1385. |
| APA | Liu, Derong,Yang, Xiong,Wang, Ding,&Wei, Qinglai.(2015).Reinforcement-Learning-Based Robust Controller Design for Continuous-Time Uncertain Nonlinear Systems Subject to Input Constraints.IEEE TRANSACTIONS ON CYBERNETICS,45(7),1372-1385. |
| MLA | Liu, Derong,et al."Reinforcement-Learning-Based Robust Controller Design for Continuous-Time Uncertain Nonlinear Systems Subject to Input Constraints".IEEE TRANSACTIONS ON CYBERNETICS 45.7(2015):1372-1385. |
入库方式： OAI收割
来源：自动化研究所
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