本方案把神经网络控制的学习机制以及模糊控制的人类思维和推理结合起来，用神经网络实现隶属，驱动模糊推理，利用神经网络的模糊建模，达到求精模糊规则的目的。由此可以看出，模糊控制在加热炉中的应用是可行的：一方面，它可以改善控制效果，提高控制精度，从而减小板坯的头尾温差，提高板坯温度的均匀性；另一方面，它可以降低系统燃料消耗，提高成材率，达到节能环保的目的。
This scheme combine the learning mechanism of neural network control with the human thinking and rea-soning of fuzzy control .Neural network is used to implement membership function ,and drive the fuzzy reasoning .U-sing neural network ,fuzzy modeling ,achieve the goal of refinement fuzzy rules .Thus it can be seen that the fuzzy control in the application of heating furnace is feasible ,on the one hand ,it can improve the control effect ,improve the control precision ,thus reducing the slab end temperature difference ,improving the uniformity of the slab tempera-ture ,on the other hand ,it can reduce the fuel consumption of the system ,improve the yield and achieve the goal of energy conservation and environmental protection .
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