Model-Free Reinforcement Learning by Embedding an Auxiliary System for Optimal Control of Nonlinear Systems
文献类型：期刊论文
| 作者 | Xu, Zhenhui2; Shen, Tielong2; Cheng, Daizhan1 |
| 刊名 | IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
 |
| 出版日期 | 2022-04-01 |
| 卷号 | 33期号:4页码:1520-1534 |
| 关键词 | Mathematical model Trajectory Heuristic algorithms Optimal control System dynamics Artificial neural networks Convergence Approximate optimal control design auxiliary trajectory completely model-free integral reinforcement learning (IRL) |
| ISSN号 | 2162-237X |
| DOI | 10.1109/TNNLS.2020.3042589 |
| 英文摘要 | In this article, a novel integral reinforcement learning (IRL) algorithm is proposed to solve the optimal control problem for continuous-time nonlinear systems with unknown dynamics. The main challenging issue in learning is how to reject the oscillation caused by the externally added probing noise. This article challenges the issue by embedding an auxiliary trajectory that is designed as an exciting signal to learn the optimal solution. First, the auxiliary trajectory is used to decompose the state trajectory of the controlled system. Then, by using the decoupled trajectories, a model-free policy iteration (PI) algorithm is developed, where the policy evaluation step and the policy improvement step are alternated until convergence to the optimal solution. It is noted that an appropriate external input is introduced at the policy improvement step to eliminate the requirement of the input-to-state dynamics. Finally, the algorithm is implemented on the actor-critic structure. The output weights of the critic neural network (NN) and the actor NN are updated sequentially by the least-squares methods. The convergence of the algorithm and the stability of the closed-loop system are guaranteed. Two examples are given to show the effectiveness of the proposed algorithm. |
| 资助项目 | JSPS KAKENHI[17H03284] |
| WOS研究方向 | Computer Science ; Engineering |
| 语种 | 英语 |
| WOS记录号 | WOS:000778930100016 |
| 出版者 | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC |
| 源URL | [http://ir.amss.ac.cn/handle/2S8OKBNM/60285]  |
| 专题 | 中国科学院数学与系统科学研究院 |
| 通讯作者 | Xu, Zhenhui |
| 作者单位 | 1.Chinese Acad Sci, Acad Math & Syst Sci, Key Lab Syst & Control, Beijing 100190, Peoples R China 2.Sophia Univ, Dept Engn & Appl Sci, Tokyo 1028554, Japan |
| 推荐引用方式 GB/T 7714 | Xu, Zhenhui,Shen, Tielong,Cheng, Daizhan. Model-Free Reinforcement Learning by Embedding an Auxiliary System for Optimal Control of Nonlinear Systems[J]. IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS,2022,33(4):1520-1534. |
| APA | Xu, Zhenhui,Shen, Tielong,&Cheng, Daizhan.(2022).Model-Free Reinforcement Learning by Embedding an Auxiliary System for Optimal Control of Nonlinear Systems.IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS,33(4),1520-1534. |
| MLA | Xu, Zhenhui,et al."Model-Free Reinforcement Learning by Embedding an Auxiliary System for Optimal Control of Nonlinear Systems".IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS 33.4(2022):1520-1534. |
入库方式： OAI收割
来源：数学与系统科学研究院
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