一种新型的神经网络在工业加热炉中的应用

Application of a New Kind of Neural Network Control in Electrical Heating Furnace

针对工业控制过程中较为常见的一种控制过程—电加热炉的炉温控制,采用了一种基于模糊基函数的模糊神经网络控制器,并给出了应用于此模糊神经网络的自学习算法。最后,将该模糊神经网络控制器应用于实际的工业加热炉炉温控制系统中。应用结果表明,该控制方案可改善具有时变及大滞后的炉温控制系统,特别是对于一些缺乏先验知识的实际工业控制过程,该控制策略具有良好的控制效果。

To temperature control, one of most common control scheme in industrial control process, a fuzzy neural network controller is presented based on fuzzy basis function. And a self-learning algorithm is given to the fuzzy neural network. The new method is used in controlling the industrial electrical heating furnace temperature. The results show that this method can improve the performance and effectiveness of the temperature control system. Especially to some practical industrial control processes with few preknowledge,the control effectiveness is better.