Control enhancement of an elliptically bent hard x-ray dynamic mirror bender with machine-learning techniques

Sheikh T. Mashrafi; Ross Harder; Xianbo Shi; Deming Shu; Zhi Qiao; Max Wyman; Tim Mooney; Jayson Anton; Steven Kearney; Luca Rebuffi; Jun Qian; Bing Shi; Lahsen Assoufid

doi:10.1117/12.2594827

21 September 2021 Control enhancement of an elliptically bent hard x-ray dynamic mirror bender with machine-learning techniques

Sheikh T. Mashrafi, Ross Harder, Xianbo Shi, Deming Shu, Zhi Qiao, Max Wyman, Tim Mooney, Jayson Anton, Steven Kearney, Luca Rebuffi, Jun Qian, Bing Shi, Lahsen Assoufid

Author Affiliations +

Proceedings Volume 11837, Advances in X-Ray/EUV Optics and Components XVI; 118370E (2021) https://doi.org/10.1117/12.2594827
Event: SPIE Optical Engineering + Applications, 2021, San Diego, California, United States

Abstract

The hard X-ray adaptive mirror optics will play an important role at next generation light sources. A dynamic mirror bender with capacitive sensor array as an in-situ mirror profiler is used for initial test for hard x-ray zoom optics has been designed and constructed. Previous work showcases the dynamic control of this elliptically bent hard X-ray mirror through applying a combination of neural networks algorithm and feedback control. In this paper, we present further control enhancement with machine learning techniques through optimization of the number and placement of the capacitive sensors and new sensor calibration with video-based coordinate measuring machine.

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Sheikh T. Mashrafi, Ross Harder, Xianbo Shi, Deming Shu, Zhi Qiao, Max Wyman, Tim Mooney, Jayson Anton, Steven Kearney, Luca Rebuffi, Jun Qian, Bing Shi, and Lahsen Assoufid "Control enhancement of an elliptically bent hard x-ray dynamic mirror bender with machine-learning techniques", Proc. SPIE 11837, Advances in X-Ray/EUV Optics and Components XVI, 118370E (21 September 2021); https://doi.org/10.1117/12.2594827

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