Fuzzy neural adaptive controller design: with application to multiple-link robot control

Author

Hsu, Ya-Chen ; Chen, Guanrong ; Malki, Heider A.

Author_Institution

Dept. of Electr. & Comput. Eng., Houston Univ., TX, USA

Volume

3

fYear

1997

fDate

9-12 Jun 1997

Firstpage

1705

Abstract

An adaptive control algorithm based on the sliding mode principle, equipped with fuzzy logic to handle system modeling uncertainties, is developed in this paper. Along with a neural-network learning scheme that enhances the adaptive control capability, this controller performs satisfactory tracking control for a large class of robot models that contain significant but unknown friction and disturbances. Both mathematical analysis and computer simulation are enclosed for demonstration

Keywords

adaptive control; closed loop systems; control system synthesis; fuzzy control; learning (artificial intelligence); manipulator dynamics; neurocontrollers; position control; robust control; uncertain systems; variable structure systems; fuzzy logic; fuzzy neural adaptive controller; modeling uncertainties; multiple-link robot control; sliding mode principle; tracking control; unknown disturbances; unknown friction; Adaptive control; Friction; Fuzzy control; Fuzzy logic; Mathematical analysis; Modeling; Programmable control; Robots; Sliding mode control; Uncertainty;

fLanguage

English

Publisher

ieee

Conference_Titel

Neural Networks,1997., International Conference on

Conference_Location

Houston, TX

Print_ISBN

0-7803-4122-8

Type

conf

DOI

10.1109/ICNN.1997.614152

Filename

614152