Research on frequency stabilization method of PID controller based on BP neural network optimization for POINT system on EAST

Abstract To ensure the accuracy and stability of electron density measurement by the laser-aided diagnostic system like polarimeter/interferometer (POINT) during the Experimental Advanced Superconducting Tokamak (EAST) experiment campaigns, a real-time laser frequency stabilization hardware solution is proposed in detail in this paper. The device is based on an incremental Proportional-Integral-Derivative (PID) control method tuned by the Back Propagation (BP) neural network, which stabilizes the intermediate-frequency (IF) of the lasers at the target value. Firstly, a real-time data acquisition and frequency calculation module is designed and implemented. Then, the BP neural network is used to calculate and output an appropriate control rate value for the current frequency. After appropriate adjustment according to this value, it is output to the digital-to-analog converter and finally applied to the piezo-electric transducer of the laser, so as to precisely adjust the length of the laser cavity and realize the stable control of the IF. The results indicate that the proposed method has achieved a rapid and stable adjustment of the POINT laser system. The control method meets the control requirements of stabilization with well self-adaptation ability and dynamic performance for POINT system on EAST.