生成对抗网络与模糊PID的层流冷却温度控制研究

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

    • 摘要: 针对层流冷却过程中存在工况变化、强非线性等复杂因素对温度合理控制的干扰,提出了一种Wasserstein生成对抗网络(Wasserstein-Generative Adversarial Nets,WGAN)和模糊自整定PID结合的优化控制方法。首先,采用蚁群算法优化模糊PID的隶属度函数和模糊规则,输出PID控制器修正因子,提升温度系统的控制精度。随后,利用博弈对抗策略优化WGAN控制器,提升系统的稳定性。仿真实验表明:该算法可有效提高系统响应速率,提升抗干扰能力,使温度控制精度和系统稳定性得到提高。

       

      Abstract: 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.

       

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