Chinese Journal of Lasers, Volume. 47, Issue 1, 0105001(2020)
Self-Learning Control Model for Adaptive Optics Systems and Experimental Verification
In adaptive optics systems, the traditional proportional-integral control model relies on the response matrix of the deformable mirror, which is sensitive to changes in the system state. When the response matrix is altered, the wavefront correction performance is degraded. In this paper, the output of control signal from Hartman slope data is realized by redefining the back-propagation neural network structure, and a control model is established. Experimental results show that the proposed model eliminates the limitation of the traditional fixed model and acquires the characteristics of an online real-time update response model. The control model delivers high convergence performance, can adapt to environmental changes, and is robust. It also improves the control precision and the control performance to a certain extent.
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Zhenxing Xu, Ping Yang, Tao Cheng, Bing Xu, Heping Li. Self-Learning Control Model for Adaptive Optics Systems and Experimental Verification[J]. Chinese Journal of Lasers, 2020, 47(1): 0105001
Category: beam transmission and control
Received: Jun. 26, 2019
Accepted: Sep. 26, 2019
Published Online: Jan. 9, 2020
The Author Email: Zhenxing Xu (xyhf2009@foxmail.com), Ping Yang (pingyang2516@163.com)