Research on Dynamic Anti-Surge Control Method of Centrifugal Compressor Based on PLC and Particle Swarm Optimization Algorithm

Aiming at the problems of delayed response and insufficient control accuracy of traditional anti-surge control of centrifugal compressor, this study proposes a dynamic anti-surge control method based on PLC and improved particle swarm optimization algorithm. By introducing dynamic inertia weight and adaptive learning factor, the particle swarm search strategy is optimized to improve the global optimization ability and convergence speed of the algorithm. An anti-surge control system is built, and the method is compared with traditional PID control and ordinary particle swarm optimization algorithm control under normal working conditions and load mutation conditions by combining MATLAB/Simulink and PLC joint simulation platform. Simulation data show that under load mutation conditions, this method shortens the surge suppression time by 62.8% compared with traditional PID control and reduces the pressure fluctuation amplitude by 77.3%; compared with the ordinary particle swarm optimization algorithm, the surge suppression time is shortened by 26.5% and the pressure fluctuation amplitude is reduced by 33.2%. The results show that the control method significantly improves the dynamic response performance and stability of the anti-surge control of centrifugal compressors, and provides a new technical solution for industrial applications.