The adaptive sliding mode control based on a fuzzy neural network for manipulators

Author

Xu, Hongbing ; Sun, Fuchun ; Sun, Zengqi

Author_Institution

Dept. of Comput. Sci. & Technol., Tsinghua Univ., Beijing, China

Volume

3

fYear

1996

fDate

14-17 Oct 1996

Firstpage

1942

Abstract

In this paper, a new control scheme for the computer control of a robot manipulator is provided, where a fuzzy neural network is used to identify the robot dynamics, a feedforward central algorithm is designed to compensate for variations in mass, gravity, Coriolis and centrifugal terms, and the discrete sliding mode control is applied to reduce further the remaining system uncertainty for precise position tracking. The whole control algorithms are developed in a discrete-time form which is very suitable for the computer control of robot manipulators

Keywords

adaptive control; discrete time systems; fuzzy control; fuzzy neural nets; manipulator dynamics; neurocontrollers; position control; variable structure systems; adaptive control; discrete time systems; dynamics; feedforward central algorithm; fuzzy neural network; manipulators; position tracking; sliding mode control; Adaptive control; Centralized control; Control systems; Fuzzy control; Fuzzy neural networks; Manipulators; Programmable control; Robot control; Sliding mode control; Weight control;

fLanguage

English

Publisher

ieee

Conference_Titel

Systems, Man, and Cybernetics, 1996., IEEE International Conference on

Conference_Location

Beijing

ISSN

1062-922X

Print_ISBN

0-7803-3280-6

Type

conf

DOI

10.1109/ICSMC.1996.565418

Filename

565418