A real-time tracking controller for piezoelectric actuators based on reinforcement learning and inverse compensation
文献类型：期刊论文
| 作者 | Qin, Shijie; Cheng, Long1
|
| 刊名 | SUSTAINABLE CITIES AND SOCIETY
 |
| 出版日期 | 2021-06-01 |
| 卷号 | 69页码:9 |
| 关键词 | Piezoelectric actuators Real-time tracking control Reinforcement learning Adaptive dynamic programming Hysteresis compensation |
| ISSN号 | 2210-6707 |
| DOI | 10.1016/j.scs.2021.102822 |
| 通讯作者 | Cheng, Long(long.cheng@ia.ac.cn) |
| 英文摘要 | Nanotechnology is a promising technology and has been widely applied for sustainable smart cities. As the fundamental devices for nanotechnology, piezoelectric actuators (PEAs) have gained wide attention in precision manufacturing because of the advantages of rapid response, large mechanical force and high resolution. However, the inherent nonlinearities of PEAs hinder wide applications for nano-positioning and high-precision manipulation. To eliminate these nonlinearities, various control methods have been proposed, while the optimal control of PEAs is considered rarely. Inspired by the reinforcement learning, adaptive dynamic programming (ADP) is proposed to solve the optimal tracking control problem of PEAs. In this paper, a controller based on reinforcement learning and inverse compensation is designed for the tracking control of PEAs. The experiments on the PEA platform are designed to verify the effectiveness of the proposed method. Comparisons with some representative controllers have demonstrated that the proposed controller has a better control performance. |
| WOS关键词 | MODEL-PREDICTIVE CONTROL ; HYSTERESIS ; PIEZOSTAGE |
| 资助项目 | National Natural Science Foundation of China[62025307] ; National Natural Science Foundation of China[U1913209] ; National Natural Science Foundation of China[61873268] ; Beijing Municipal Natural Science Foundation, China[JQ19020] |
| WOS研究方向 | Construction & Building Technology ; Science & Technology - Other Topics ; Energy & Fuels |
| 语种 | 英语 |
| WOS记录号 | WOS:000689066400008 |
| 出版者 | ELSEVIER |
| 资助机构 | National Natural Science Foundation of China ; Beijing Municipal Natural Science Foundation, China |
| 源URL | [http://ir.ia.ac.cn/handle/173211/45902]  |
| 专题 | 自动化研究所_复杂系统管理与控制国家重点实验室_先进机器人控制团队 |
| 通讯作者 | Cheng, Long |
| 作者单位 | 1.Chinese Acad Sci, Inst Automat, State Key Lab Control & Management Complex Syst, Beijing 100190, Peoples R China 2.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing 100190, Peoples R China |
| 推荐引用方式 GB/T 7714 | Qin, Shijie,Cheng, Long. A real-time tracking controller for piezoelectric actuators based on reinforcement learning and inverse compensation[J]. SUSTAINABLE CITIES AND SOCIETY,2021,69:9. |
| APA | Qin, Shijie,&Cheng, Long.(2021).A real-time tracking controller for piezoelectric actuators based on reinforcement learning and inverse compensation.SUSTAINABLE CITIES AND SOCIETY,69,9. |
| MLA | Qin, Shijie,et al."A real-time tracking controller for piezoelectric actuators based on reinforcement learning and inverse compensation".SUSTAINABLE CITIES AND SOCIETY 69(2021):9. |
入库方式： OAI收割
来源：自动化研究所
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