Title :
A hybrid fuzzy neural network and its control applications
Author :
Chuang, C.-H. ; Lee, T.S.
Author_Institution :
Sch. of Aerosp. Eng., Georgia Inst. of Technol., Atlanta, GA, USA
Abstract :
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
Keywords :
fuzzy logic; fuzzy neural nets; inference mechanisms; multilayer perceptrons; neurocontrollers; approximation performance; general fuzzy inference system; gradient method; hybrid fuzzy neural network; inverted pendulum control problem; learning algorithms; modified multilayer feedforward neural network; temporal backpropagation; Feedforward neural networks; Fuzzy control; Fuzzy neural networks; Fuzzy systems; Gradient methods; Hafnium; Inference algorithms; Multi-layer neural network; Neural networks; Neurons;
Conference_Titel :
Intelligent Control, 1996., Proceedings of the 1996 IEEE International Symposium on
Conference_Location :
Dearborn, MI
Print_ISBN :
0-7803-2978-3
DOI :
10.1109/ISIC.1996.556197
