A Recurrent Fuzzy Neural Network Based Adaptive Control and Its Application on Robotic Tracking Control
نویسندگان
چکیده
Abstract— A kind of recurrent fuzzy neural network (RFNN) is constructed by using recurrent neural network (RNN) to realize fuzzy inference. In this kind of RFNN, temporal relations are embedded in the network by adding feedback connections on the first layer of the network. And a RFNN based adaptive control (RFNNBAC) is proposed, in which, two RFNN are used to identify and control plant respectively. Simulation experiments are made by applying proposed RFNNBAC on robotic tracking control problem to confirm its effectiveness.
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