A real-time tracking controller for piezoelectric actuators based on reinforcement learning and inverse compensation

doi:10.1016/j.scs.2021.102822

CORC > 自动化研究所 > 中国科学院自动化研究所 > 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

	A real-time tracking controller for piezoelectric actuators based on reinforcement learning and inverse compensation
	Qin, Shijie ; Cheng, Long 1
刊名	SUSTAINABLE CITIES AND SOCIETY
	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.
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关键词	MODEL-PREDICTIVE CONTROL ; HYSTERESIS ; PIEZOSTAGE
WOS研究方向	Construction & Building Technology ; Science & Technology - Other Topics ; Energy & Fuels
语种	英语
出版者	ELSEVIER
WOS记录号	WOS:000689066400008
资助机构	National Natural Science Foundation of China ; Beijing Municipal Natural Science Foundation, China
内容类型	期刊论文
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.