用递归模糊小波神经网络控制交流伺服系统

2006 CES/IEEE 5th International Power Electronics and Motion Control Conference Pub Date : 2006-08-01 DOI:10.1109/IPEMC.2006.4778115

Yan Tang, Wei Sun, Yaonan Wang, X. Zhai

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引用次数: 0

摘要

利用递归小波神经网络实现模糊推理，构造了一种递归模糊小波神经网络(RFWNN)。在网络中，通过在网络的第一层添加反馈连接，将时间关系嵌入到网络中，并使用小波基函数作为模糊隶属函数。提出了一种基于RFWNN的自适应控制方案，该方案采用两个RFWNN分别对被控对象进行识别和控制。将所提出的自适应控制方案应用于交流伺服控制问题，并给出了仿真结果

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Using Recurrent Fuzzy Wavelet Neural Network to Control AC Servo System

A kind of recurrent fuzzy wavelet neural network (RFWNN) is constructed by using recurrent wavelet neural network (RWNN) to realize fuzzy inference. In the network, temporal relations are embedded in the network by adding feedback connections on the first layer of the network, and wavelet basis function is used as fuzzy membership function. An adaptive control scheme based on RFWNN is proposed, in which, two RFWNN are used to identify and control plant respectively. The proposed adaptive control scheme is applied on AC servo control problem, and simulation results are given

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2006 CES/IEEE 5th International Power Electronics and Motion Control Conference

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