首页> 外文会议>International Symposium on Neural Networks(ISNN 2006) pt.2; 20060528-0601; Chengdu(CN) >Adaptive Control Based on Recurrent Fuzzy Wavelet Neural Network and Its Application on Robotic Tracking Control
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Adaptive Control Based on Recurrent Fuzzy Wavelet Neural Network and Its Application on Robotic Tracking Control

机译:基于递归模糊小波神经网络的自适应控制及其在机器人跟踪控制中的应用

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摘要

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 RFWNNs are used to identify and control plant respectively. Simulation experiments are made by applying proposed adaptive control scheme on robotic tracking control problem to confirm its effectiveness.
机译:利用递归小波神经网络(RWNN)构造一种递归模糊小波神经网络(RFWNN),实现模糊推理。在网络中,通过在网络的第一层添加反馈连接,将时间关系嵌入网络中,并将小波基函数用作模糊隶属函数。提出了一种基于RFWNN的自适应控制方案,其中两个RFWNN分别用于设备的识别和控制。通过将提出的自适应控制方案应用于机器人跟踪控制问题进行仿真实验,以验证其有效性。

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