一种递归模糊神经网络自适应控制方法

An Adaptive Control Using Recurrent Fuzzy Neural Network

构造了一种递归模糊神经网络(RFNN),该RFNN利用递归神经网络实现模糊推理,并通过在网络的第一层添加了反馈连接,使网络具有了动态信息处理能力.基于所设计的RFNN,提出了一种自适应控制方案,在该控制方案中,采用了两个RFNN分别用于对被控对象进行辨识和控制.将所提出的自适应控制方案应用于交流伺服系统,并给出了仿真实验结果,验证了所提方法的有效性.

A kind of recurrent fuzzy neural network （RFNN） is constructed, in which, recurrent neural network is used to realize fuzzy inference and temporal relations are embedded in the network by adding feedback connections on the first layer of the network. On the basis of the proposed RFNN, an adaptive control scheme is proposed,in which,two proposed RFNNs are used to identify and control plant respectively. Simulation experiments are made by applying proposed adaptive control scheme on AC servo control problem to confirm its effectiveness.