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退火炉的自动控制策略已成为过程控制的研究热点。由于退火炉是一个大惯性、纯滞后、参数时变的非线性控制对象,很难准确建立起炉子的精确数学模型,根据退火炉工业系统的特点,采用了模糊PID参数自调整控制的控制方法,将其应用于退火炉温度控制环节。本文利用Simulink对模糊神经网络PID控制算法进行仿真试验。试验显示,模糊神经网络控制算法能够展现强抗干扰性、强鲁棒性以及良好的控制性能,适用于对退火炉的温度控制中。
Annealing furnace automatic control strategy has become the research focus of process control. Because the annealing furnace is a non-linear control object with large inertia, pure hysteresis and time-varying parameters, it is very difficult to accurately establish the accurate mathematical model of the furnace. According to the characteristics of annealing furnace industrial system, the fuzzy PID parameter self-adjusting control method , It is applied to the annealing furnace temperature control. In this paper, Simulink fuzzy neural network PID control algorithm simulation test. Experiments show that the fuzzy neural network control algorithm can show strong anti-interference, strong robustness and good control performance, suitable for annealing furnace temperature control.