Deep learning control model for adaptive optics systems

doi:10.1364/AO.58.001998

CORC > 光电技术研究所 > 中国科学院光电技术研究所 > 自适应光学技术研究室（八室）

	Deep learning control model for adaptive optics systems
	Xu, Zhenxing 1,2,3,4; Yang, Ping 1,2,4; Hu, Ke 1,2,4; Xu, Bing 1,2,4; Li, Heping 3
刊名	Applied Optics
	2019-03-10
卷号	58 期号:8 页码:1998-2009
ISSN号	1559-128X
DOI	10.1364/AO.58.001998
文献子类	期刊论文
英文摘要	To correct wavefront aberrations, commonly employing proportional-integral control in adaptive optics (AO) systems, the control process depends strictly on the response matrix of the deformable mirror. The alignment error between the Hartmann–Shack wavefront sensor and the deformable mirror is caused by various factors in AO systems. In the conventional control method, the response matrix can be recalibrated to reduce the impact of alignment error, but the impact cannot be eliminated. This paper proposes a control method based on a deep learning control model (DLCM) to compensate for wavefront aberrations, eliminating the dependence on the deformable mirror response matrix. Based on the wavefront slope data, the cost functions of the model network and the actor network are defined, and the gradient optimization algorithm improves the efficiency of the network training. The model network guarantees the stability and convergence speed, while the actor network improves the control accuracy, realizing an online identification and self-adaptive control of the system. A parameter-sharing mechanism is adopted between the model network and the actor network to control the system gain. Simulation results show that the DLCM has good adaptability and stability. Through self-learning, it improves the convergence accuracy and iterations, as well as the adjustment tolerance of the system. © 2019 Optical Society of America.
WOS研究方向	Optics
语种	英语
出版者	OSA - The Optical Society
WOS记录号	WOS:000460622500018
内容类型	期刊论文
源URL	[http://ir.ioe.ac.cn/handle/181551/9667]
专题	光电技术研究所_自适应光学技术研究室（八室）
作者单位	1.University of Chinese Academy of Sciences, Beijing; 100039, China 2.Key Laboratory on Adaptive Optics, Chinese Academy of Sciences, Chengdu; 610209, China; 3.School of Optoelectronic Science and Engineering, University of Electronic Science and Technology of China, Chengdu; 610054, China; 4.Institute of Optics and Electronics, Chinese Academy of Sciences, Chengdu; 610209, China;
推荐引用方式 GB/T 7714	Xu, Zhenxing,Yang, Ping,Hu, Ke,et al. Deep learning control model for adaptive optics systems[J]. Applied Optics,2019,58(8):1998-2009.
APA	Xu, Zhenxing,Yang, Ping,Hu, Ke,Xu, Bing,&Li, Heping.(2019).Deep learning control model for adaptive optics systems.Applied Optics,58(8),1998-2009.
MLA	Xu, Zhenxing,et al."Deep learning control model for adaptive optics systems".Applied Optics 58.8(2019):1998-2009.