Monte Carlo-based reinforcement learning control for unmanned aerial vehicle systems
文献类型：期刊论文
| 作者 | Wei, Qinglai2,3,4 ; Yang, Zesheng3,4; Su, Huaizhong1; Wang, Lijian1
|
| 刊名 | NEUROCOMPUTING
 |
| 出版日期 | 2022-10-01 |
| 卷号 | 507页码:282-291 |
| 关键词 | Reinforcement learning Adaptive dynamic programming (ADP) UAV control Monte Carlo simulation Neural networks |
| ISSN号 | 0925-2312 |
| DOI | 10.1016/j.neucom.2022.08.011 |
| 通讯作者 | Wei, Qinglai(qinglai.wei@ia.ac.cn) |
| 英文摘要 | In this paper, a new data-driven reinforcement learning method based on Monte Carlo simulation is developed to solve the optimal control problem of unmanned aerial vehicle (UAV) systems. Based on the data which are generated by Monte Carlo simulation, neural network (NN) is used to construct the dynamics of the UAV system with unknown disturbances, where the mathematical model of the UAV sys-tem is unnecessary. An effective iterative framework of action and critic is constructed to obtain the opti-mal control law. The convergence property is developed to guarantee that the iterative performance cost function converges to a finite neighborhood of the optimal performance cost function. Finally, numerical results are given to illustrate the effectiveness of the developed method.(c) 2022 Published by Elsevier B.V. |
| WOS关键词 | LINEAR MULTIAGENT SYSTEMS ; NEURAL-NETWORK ; NONLINEAR-SYSTEMS ; QUADROTOR ; UAV ; CONSENSUS ; DYNAMICS ; TRACKING ; DESIGN ; GAMES |
| 资助项目 | National Key R&D Pro- gram of China[2021YFE0206100] ; National Key R&D Pro- gram of China[2018YFB1702300] ; National Natural Science Founda- tion of China[62073321] ; National Defense Basic Scientific Research Program[JCKY2019203C029] ; Science and Technology Development Fund, Macau SAR[0015/2020/AMJ] |
| WOS研究方向 | Computer Science |
| 语种 | 英语 |
| WOS记录号 | WOS:000843489800008 |
| 出版者 | ELSEVIER |
| 资助机构 | National Key R&D Pro- gram of China ; National Natural Science Founda- tion of China ; National Defense Basic Scientific Research Program ; Science and Technology Development Fund, Macau SAR |
| 源URL | [http://ir.ia.ac.cn/handle/173211/49882]  |
| 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 | Wei, Qinglai |
| 作者单位 | 1.Beijing Aeronaut Technol Res Inst COMAC, Beijing 102211, Peoples R China 2.Macau Univ Sci & Technol, Inst Syst Engn, Macau 999078, Peoples R China 3.Univ Chinese Acad Sci, Beijing 100049, Peoples R China 4.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 | Wei, Qinglai,Yang, Zesheng,Su, Huaizhong,et al. Monte Carlo-based reinforcement learning control for unmanned aerial vehicle systems[J]. NEUROCOMPUTING,2022,507:282-291. |
| APA | Wei, Qinglai,Yang, Zesheng,Su, Huaizhong,&Wang, Lijian.(2022).Monte Carlo-based reinforcement learning control for unmanned aerial vehicle systems.NEUROCOMPUTING,507,282-291. |
| MLA | Wei, Qinglai,et al."Monte Carlo-based reinforcement learning control for unmanned aerial vehicle systems".NEUROCOMPUTING 507(2022):282-291. |
入库方式： OAI收割
来源：自动化研究所
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