Research on Laminar Cooling Temperature Control Based on Generative Adversarial Network and Fuzzy PID

An optimal control method combining Wasserstein-Generative Adversarial Nets（WGAN） and fuzzy self-tuning PID was proposed to solve the interference of complex factors such as work condition variation and strong nonlinearity on the rational control of temperature in the laminar cooling process. Firstly, the ant colony algorithm was used to optimize the membership function and fuzzy rules of fuzzy PID, and the PID controller correction factor was output to improve the control accuracy of temperature system. Then the WGAN controller was optimized by game adversarial strategy to improve the stability of the system. The simulation results show that the algorithm can effectively improve the response rate of the system,improve the anti-interference ability and improve the temperature control accuracy and system stability.