Temperature Control Performance Improvement of High-Power Laser Diode with Assistance of Machine Learning

• DOI: 10.3390/photonics12030241
• Publication Date: 2025-03-07T09:29:59Z
• Authors: Yaohui He; Xiaoli Jin; Pixian Jin; Jing Su; Fang Li; Huadong Lu

For a laser diode (LD) with high output power, it is difficult to precisely and quickly control its temperature because of the large thermal power involved. In this paper, machine learning-based controller for high-power LDs reported. It implemented by developing back-propagation neural network (BPNN) an adaptive dynamic adjustment strategy (ADAS) which integrates constant-current-source circuit into conventional proportional-integral-derivative (PID) temperature-controlling circuit. Compared PID controller, speed had been shortened from 1300 s 350 s, long-term fluctuation was decreased ±0.148% ±0.082%, step response time could be 960 210 s.