一种模糊人工神经网络控制器的设计与研究

Designing and Researching for a FANNC

模糊控制与人工神经网络控制有许多相似之处，如何最大程度地发挥这两种控制的优点是一个很重要的问题。本文利用模糊控制算法快速、简便的优点弥补了人工神经网络算法复杂、缓慢的缺点，利用神经元特征函数使模糊控制更容易处理，以此为基础研制出一种模糊人工神经网络控制器（简称ＦＡＮＮＣ）．通过仿真验证了该ＦＡＮＮＣ的合理性，其控制效果明显优于文献［８］的控制效果。同时，也表明模糊控制是一种特殊的人工神经网络控制，二者是一致的，其学习和训练可以用相同的方法来进行，这对二者的统一处理很有价值。

Fuzzy control is similar to artificial neural network control on many aspects. It is very important to exert their advantages. This paper uses the high-speed and concise properties of fuzzy control to make up the low-speed and complexities of artificial neural network. On the other hand, neural activation function makes it easy to deal with fuzzy control. Based on these advantages,a new fuzzy artificial neural network controller (FANNC) is designed. Its reasonableness is verified by simulation. The simulation results of FANNC are superior to literature[8]. Also, this paper shows that fuzzy control is a kind of special artificial neural network, they can be trained in the same way. It is very valuable for united dealing with both of them.