A fuzzy-Gaussian neural network and its application to mobile robot control

Author

Watanabe, Keigo ; Tang, Jun ; Nakamura, Masatoshi ; Koga, Shinji ; Fukuda, Toshio

Author_Institution

Dept. of Mech. Eng., Saga Univ., Japan

Volume

4

Issue

2

fYear

1996

fDate

3/1/1996 12:00:00 AM

Firstpage

193

Lastpage

199

Abstract

A fuzzy-Gaussian neural network (FGNN) controller is described by applying a Gaussian function as an activation function. A specialized learning architecture is used so that membership function can be tuned without using expert´s manipulated data. As an example of the application, a tracking control problem for the speed and azimuth of a mobile robot driven by two independent wheels is solved by using the FGNN controller. To simplify the implementation of the FGNN controller for the two-input/two-output controlled system, a learning controller is utilized consisting of two FGNN´s based on independent reasoning and a connection net with fixed weights. The effectiveness of the proposed method is illustrated by performing the simulation of a circular or square trajectory tracking control

Keywords

fuzzy control; fuzzy neural nets; learning (artificial intelligence); mobile robots; neurocontrollers; activation function; fuzzy-Gaussian neural network; membership function; mobile robot control; specialized learning architecture; tracking control; trajectory tracking control; two-input/two-output controlled system; Automatic control; Azimuth; Control systems; Fuzzy control; Fuzzy neural networks; Fuzzy reasoning; Mobile robots; Neural networks; Optimal control; Robot control;

fLanguage

English

Journal_Title

Control Systems Technology, IEEE Transactions on

Publisher

ieee

ISSN

1063-6536

Type

jour

DOI

10.1109/87.486346

Filename

486346