Adaptive fuzzy neural controller design

Author

Wang, Dianhui ; Chai, Tianpou ; Xia, Lihua

Author_Institution

Res. Center of Autom., Northeastern Univ., Shenyang, China

Volume

6

fYear

1995

fDate

21-23 Jun 1995

Firstpage

4258

Abstract

A new design approach for adaptive fuzzy logic controller (AFLC) based on neural-net concept is presented in this work. The main ideas of our proposed strategy include: (1) connectionist implementation of fuzzy logic controller (FLC) using a simplified fuzzy inference network (SFIN); (2) initialisation of the AFLC using supervised learning control; and (3) online adaptation of the AFLC using GPC performance index. A nonlinear plant with nonminimum phase characteristics and uncertainties is employed in our simulations. The observed results demonstrate the effectiveness at the presented AFLC

Keywords

adaptive control; fuzzy control; fuzzy neural nets; neurocontrollers; adaptive fuzzy neural controller design; connectionist implementation; initialisation; neural net; nonminimum phase characteristics; performance index; simplified fuzzy inference network; supervised learning control; uncertainties; Adaptive control; Automatic control; Fuzzy control; Fuzzy logic; Fuzzy neural networks; Humans; Industrial control; Process control; Programmable control; Uncertainty;

fLanguage

English

Publisher

ieee

Conference_Titel

American Control Conference, Proceedings of the 1995

Conference_Location

Seattle, WA

Print_ISBN

0-7803-2445-5

Type

conf

DOI

10.1109/ACC.1995.532737

Filename

532737