A PID algorithm based on convolutional neural network for pointing stabilization control of synchrotron radiation beams

Zhaohui Hu; Gaoqi Liang; Qinglei Xiu; Yadong Wei

doi:10.1117/12.3026018

1 April 2024 A PID algorithm based on convolutional neural network for pointing stabilization control of synchrotron radiation beams

Zhaohui Hu, Gaoqi Liang, Qinglei Xiu, Yadong Wei

Author Affiliations +

Proceedings Volume 13082, Fourth International Conference on Mechanical Engineering, Intelligent Manufacturing, and Automation Technology (MEMAT 2023); 130823A (2024) https://doi.org/10.1117/12.3026018
Event: 2023 4th International Conference on Mechanical Engineering, Intelligent Manufacturing and Automation Technology (MEMAT 2023), 2023, Guilin, China

Abstract

A PID algorithm using a fixed set of parameters in synchrotron radiation beam control systems does not meet the need to control various environmental vibrations. This study proposes a vibration identification method based on convolutional neural network(CNN) to improve the PID algorithm. Firstly, the genetic algorithm is used to rectify the optimal control parameters for various types of vibration in advance, and then the CNN recognizes the vibration types to assist the PID algorithm in selecting the corresponding optimal control parameters online, so as to realize the optimal control under various vibrations. A set of mixed vibration signal inputs are applied to the beam control system to detect the final beam position deviation displacement. The experiment shows that the beam deviation displacement under the improved PID method is smaller and has better results than the traditional PID control method.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Zhaohui Hu, Gaoqi Liang, Qinglei Xiu, and Yadong Wei "A PID algorithm based on convolutional neural network for pointing stabilization control of synchrotron radiation beams", Proc. SPIE 13082, Fourth International Conference on Mechanical Engineering, Intelligent Manufacturing, and Automation Technology (MEMAT 2023), 130823A (1 April 2024); https://doi.org/10.1117/12.3026018

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