Adaptive Control Based on Recurrent Fuzzy Wavelet Neural Network and Its Application on Robotic Tracking Control

Abstract

AbstractA 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.KeywordsAdaptive ControlFuzzy RuleRecurrent Neural NetworkCellular Neural NetworkRobotic ManipulatorThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.