ANFIS based modelling and control of non-linear systems : a tutorial

Author

Denaï, Mouloud A. ; Palis, Frank ; Zeghbib, Abdelhafid

Author_Institution

University of Sci. & Technol., Oran, Algeria

Volume

4

fYear

2004

fDate

10-13 Oct. 2004

Firstpage

3433

Abstract

This work is an attempt to illustrate the utility and effectiveness of soft-computing approaches in handling the modelling and control of complex systems. Soft computing research is concerned with the integration of artificial intelligent tools (neural networks, fuzzy technology, and evolutionary algorithms) in a complementary hybrid framework for solving real world problems. The present work concentrates on the pioneering neuro-fuzzy system ANFIS (adaptive neuro fuzzy inference system). ANFIS is first used to model nonlinear knee-joint dynamics from recorded clinical data. The established model is then used to predict the behaviour of the underlying system and for the design and evaluation of various intelligent control strategies.

Keywords

evolutionary computation; fuzzy logic; fuzzy neural nets; inference mechanisms; intelligent control; large-scale systems; neurocontrollers; nonlinear control systems; adaptive neuro fuzzy inference system; evolutionary algorithm; fuzzy technology; intelligent control strategy; neural networks; nonlinear knee-joint dynamics; soft-computing approach; Adaptive systems; Artificial intelligence; Artificial neural networks; Computer networks; Control system synthesis; Evolutionary computation; Fuzzy neural networks; Intelligent networks; Nonlinear control systems; Tutorial;

fLanguage

English

Publisher

ieee

Conference_Titel

Systems, Man and Cybernetics, 2004 IEEE International Conference on

ISSN

1062-922X

Print_ISBN

0-7803-8566-7

Type

conf

DOI

10.1109/ICSMC.2004.1400873

Filename

1400873