Design of fuzzy controllers with local response neurons

Author

Sitte, Joaquin ; Geva, Shlomo

Author_Institution

Fac. of Inf. Technol., Queensland Univ. of Technol., Brisbane, Qld., Australia

Volume

2

fYear

1994

fDate

2-5 Oct 1994

Firstpage

2021

Abstract

The class of artificial neural networks made up of nodes that have a localised response in input space have functional similarities with fuzzy logic controllers. The localised response nodes can be interpreted as representing membership functions. Each node represents a fuzzy rule for a control action and the network interpolates between the fuzzy rules. We illustrate the process of building a fuzzy controller for the cart-pole experiment using a local response neural net based on clusters of neurones with sigmoidal transfer functions

Keywords

control system synthesis; fuzzy control; fuzzy neural nets; transfer functions; artificial neural networks; cart-pole experiment; fuzzy controller design; interpolation; local response neurons; localised response; membership functions; neuron clusters; sigmoidal transfer functions; Artificial neural networks; Automatic control; Fuzzy control; Fuzzy logic; Fuzzy neural networks; Neural networks; Neurons; Optimal control; Quantization; Space technology; Transfer functions;

fLanguage

English

Publisher

ieee

Conference_Titel

Systems, Man, and Cybernetics, 1994. Humans, Information and Technology., 1994 IEEE International Conference on

Conference_Location

San Antonio, TX

Print_ISBN

0-7803-2129-4

Type

conf

DOI

10.1109/ICSMC.1994.400149

Filename

400149