A hybrid fuzzy neural network and its control applications

We present an alternative neural network architecture which is similar to the operation of a general fuzzy inference system. This hybrid fuzzy neural network (HFNN) is a modified multilayer feedforward neural network (MFNN) with four different layers. By using the gradient method, learning algorithm...

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Bibliographic Details
Published inProceedings of the 1996 IEEE International Symposium on Intelligent Control pp. 175 - 180
Main Authors Chuang, C.-H., Lee, T.S.
Format Conference Proceeding
LanguageEnglish
Published IEEE 1996
Subjects
Feedforward neural networks
Fuzzy control
Fuzzy neural networks
Fuzzy systems
Gradient methods
Hafnium
Inference algorithms
Multi-layer neural network
Neural networks
Neurons
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ISBN9780780329782
0780329783
ISSN2158-9860
DOI10.1109/ISIC.1996.556197

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Summary:We present an alternative neural network architecture which is similar to the operation of a general fuzzy inference system. This hybrid fuzzy neural network (HFNN) is a modified multilayer feedforward neural network (MFNN) with four different layers. By using the gradient method, learning algorithms are derived. An example is presented to compare the approximation performance of the HFNN with the MFNN. The HFNN is then applied to an inverted pendulum control problem by using temporal backpropagation. The performance of the HFNN controller is illustrated by simulations.
ISBN:9780780329782
0780329783
ISSN:2158-9860
DOI:10.1109/ISIC.1996.556197