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Auto-tuning method of fuzzy PID controller parameter based on self-learning system

机译：基于自学习系统的模糊PID控制器参数自整定方法

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摘要

In order to overcome the puzzle of optimal status being difficult to adjust after once setting PID parameters, the paper proposed a sort of auto-tuning method of fuzzy-PID parameters based on self-learning system. Combined fuzzy logic control with classical PID control, it conducted the fuzzy on-line auto-tuning of PID parameter, and after that, the parameters of adjusted system were switched to the natural work status. Once the change of system performance occurred, and it went beyond the specified range, the system could automatically start the parameters tuning process of PID. The simulation demonstrated that the retuned parameters could obtain better control effect than before. The simulation shows that it is higher in control accuracy, stronger in robustness, and the system performance is greatly enhanced.
机译：为了克服一次设置PID参数后最优状态难以调整的难题，提出了一种基于自学习系统的模糊PID参数自动整定方法。将模糊逻辑控制与经典PID控制相结合，对PID参数进行模糊在线自动整定，然后将调整后的系统参数切换为自然工作状态。一旦系统性能发生变化，并且超出了指定范围，系统将自动启动PID的参数调整过程。仿真结果表明，经过重调的参数可以获得比以往更好的控制效果。仿真表明，该方法控制精度较高，鲁棒性较强，系统性能大大提高。

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