Intelligent Thermal Control Algorithm Based on Deep Deterministic Policy Gradient for Spacecraft

doi:10.2514/1.T5951

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	Intelligent Thermal Control Algorithm Based on Deep Deterministic Policy Gradient for Spacecraft
	Y. Xiong,L. Guo,H. L. Wang,Y. Huang and C. L. Liu
刊名	Journal of Thermophysics and Heat Transfer
	2020
卷号	34 期号:4 页码:683-695
ISSN号	0887-8722
DOI	10.2514/1.T5951
英文摘要	In practical applications, it is difficult for the control parameters of the proportional integral derivative (PID) thermal controller to be self-tuning online. As the control object or environment changes, the control parameters are required to change accordingly. An intelligent thermal controller based on the deep deterministic policy gradient, called DRLTC, is proposed. Two types of reinforcement learning agents were designed in DRLTC, which can automatically adjust the control parameters of the thermal controllers and self-optimize online after training. Both theoretical and experimental results revealed that, when the control object was the main mirror support, the DRLTC achieved a control precision of 0.01 degrees C. Additionally, the steady-state error was reduced by 40.2, 62.5, and 33.3% in the simulation and by 5.6, 80.6, and 85.7% in the experiment, compared with the reinforcement learning PID, neural network PID, and adaptive PID control based on fuzzy control, respectively. When the control object was changed to the main mirror installation, the DRLTC achieved a control precision of 0.02 degrees C, and the steady-state error was reduced by 87.5, 91.7, and 90.9% in the simulation and by 80.2, 90.6, and 85.7% in the experiment, compared with the above-mentioned thermal control strategies, respectively. Therefore, the DRLTC has better universality, has stronger robustness, and saves more energy.
URL标识	查看原文
语种	英语
内容类型	期刊论文
源URL	[http://ir.ciomp.ac.cn/handle/181722/64625]
专题	中国科学院长春光学精密机械与物理研究所
推荐引用方式 GB/T 7714	Y. Xiong,L. Guo,H. L. Wang,Y. Huang and C. L. Liu. Intelligent Thermal Control Algorithm Based on Deep Deterministic Policy Gradient for Spacecraft[J]. Journal of Thermophysics and Heat Transfer,2020,34(4):683-695.
APA	Y. Xiong,L. Guo,H. L. Wang,Y. Huang and C. L. Liu.(2020).Intelligent Thermal Control Algorithm Based on Deep Deterministic Policy Gradient for Spacecraft.Journal of Thermophysics and Heat Transfer,34(4),683-695.
MLA	Y. Xiong,L. Guo,H. L. Wang,Y. Huang and C. L. Liu."Intelligent Thermal Control Algorithm Based on Deep Deterministic Policy Gradient for Spacecraft".Journal of Thermophysics and Heat Transfer 34.4(2020):683-695.