Study of PID neural network control based on phase-shifted full-bridge CPT system

Lihong He; Yingying Guo; Guangyan Sun

doi:10.1117/12.906147

28 October 2011 Study of PID neural network control based on phase-shifted full-bridge CPT system

Lihong He, Yingying Guo, Guangyan Sun

Proceedings Volume 8205, 2011 International Conference on Photonics, 3D-Imaging, and Visualization; 820517 (2011) https://doi.org/10.1117/12.906147
Event: 2011 International Conference on Photonics, 3D-imaging, and Visualization, 2011, Guangzhou, China

Abstract

Since the CPT system is a complex higher-order nonlinear system, it is very difficult to meet the control requirements if the traditional control method is used to control the stability of the system. In this paper, a performance simulation study is performed by introducing the PID neural network controller into the Phase-Shifted Full-Bridge CPT system. Compared with the control effects of traditional PID controllers, the PID neural network controllers have better dynamic responses and more robustness under load rapid changes and input step disturbances.

Citation Download Citation

Lihong He, Yingying Guo, and Guangyan Sun "Study of PID neural network control based on phase-shifted full-bridge CPT system", Proc. SPIE 8205, 2011 International Conference on Photonics, 3D-Imaging, and Visualization, 820517 (28 October 2011); https://doi.org/10.1117/12.906147

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