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设计了一种基于模糊推理进行参数自整定的PID控制器,构造了一个3层BP神经网络来学习模糊控制规则完成模糊控制的模糊推理。将该控制器应用于电阻炉的温度控制,并与普通模糊自整定PID控制器进行比较,表明该方法提高了对非线性、时滞系统的控制效果。
A PID controller based on fuzzy reasoning is designed and a 3-layer BP neural network is constructed to learn fuzzy control rules to complete the fuzzy inference of fuzzy control. The controller is applied to the temperature control of the resistance furnace and compared with the general fuzzy self-tuning PID controller, which shows that this method improves the control effect on the nonlinear and time-delay system.