Controller Optimization for Multirate Systems Based on Reinforcement Learning

doi:10.1007/s11633-020-1229-0

CASIA OpenIR > 学术期刊 > Machine Intelligence Research

	Controller Optimization for Multirate Systems Based on Reinforcement Learning
	Zhan Li 1; Sheng-Ri Xue 1; Xing-Hu Yu 1,2; Hui-Jun Gao 1
发表期刊	International Journal of Automation and Computing
ISSN	1476-8186
	2020
卷号	17 期号:3 页码:417-427
摘要	The goal of this paper is to design a model-free optimal controller for the multirate system based on reinforcement learning. Sampled-data control systems are widely used in the industrial production process and multirate sampling has attracted much attention in the study of the sampled-data control theory. In this paper, we assume the sampling periods for state variables are different from periods for system inputs. Under this condition, we can obtain an equivalent discrete-time system using the lifting technique. Then, we provide an algorithm to solve the linear quadratic regulator (LQR) control problem of multirate systems with the utilization of matrix substitutions. Based on a reinforcement learning method, we use online policy iteration and off-policy algorithms to optimize the controller for multirate systems. By using the least squares method, we convert the off-policy algorithm into a model-free reinforcement learning algorithm, which only requires the input and output data of the system. Finally, we use an example to illustrate the applicability and efficiency of the model-free algorithm above mentioned.
关键词	Multirate system reinforcement learning policy iteration optimal control controller optimization.
DOI	10.1007/s11633-020-1229-0
引用统计	被引频次：7[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.ia.ac.cn/handle/173211/42290
专题	学术期刊_Machine Intelligence Research
作者单位	1.Research Institute of Intelligent Control and Systems, Harbin Institute of Technology, Harbin 150001, China 2.Ningbo Institute of Intelligent Equipment Technology, Harbin Institute of Technology, Ningbo 315200, China
推荐引用方式 GB/T 7714	Zhan Li,Sheng-Ri Xue,Xing-Hu Yu,et al. Controller Optimization for Multirate Systems Based on Reinforcement Learning[J]. International Journal of Automation and Computing,2020,17(3):417-427.
APA	Zhan Li,Sheng-Ri Xue,Xing-Hu Yu,&Hui-Jun Gao.(2020).Controller Optimization for Multirate Systems Based on Reinforcement Learning.International Journal of Automation and Computing,17(3),417-427.
MLA	Zhan Li,et al."Controller Optimization for Multirate Systems Based on Reinforcement Learning".International Journal of Automation and Computing 17.3(2020):417-427.

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