An Adaptive Control for AC Servo System Using Recurrent Fuzzy Neural Network

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...

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Bibliographic Details
Published inAdvances in Natural Computation pp. 190 - 195
Main Authors Sun, Wei, Wang, Yaonan
Format Book Chapter Conference Proceeding
LanguageEnglish
Published Berlin, Heidelberg Springer Berlin Heidelberg 2005
Springer
SeriesLecture Notes in Computer Science
Subjects
Adaptive Control
Applied sciences
Artificial intelligence
Cellular Neural Network
Computer science; control theory; systems
Exact sciences and technology
Fuzzy Rule
Learning Automaton
Recurrent Neural Network
Recurrent neural nets
Ac motor
Feedback system
Inference
Neural network
Adaptive control
Fuzzy neural nets
Servomechanism
Servomotor
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Summary: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 AC servo control problem to confirm its effectiveness.
ISBN:9783540283256
3540283250
3540283234
9783540283232
ISSN:0302-9743
1611-3349
DOI:10.1007/11539117_29