Online RBF and fuzzy based sliding mode control of robot manipulator

Author

Salem, Mahmoud ; Khelfi, M.F.

Author_Institution

RIIR Lab., Mascara Univ., Mascara, Algeria

fYear

2012

Firstpage

896

Lastpage

901

Abstract

The aim of this work is the combination of radial basis function networks (RBF) and fuzzy techniques to enhance the sliding mode controllers. In fact, three RBFs networks were used to estimate the model parameters and to respond to model variation and disturbances, a sequential training algorithm based on Kalman filter was implemented, and to eliminate the chattering effect, a fuzzy controller was designed. The hybrid sliding mode controller had shown a strong ability to get over noise and uncertainties. The former controller was used to control a two degree of freedom robot manipulator.

Keywords

Kalman filters; control nonlinearities; control system synthesis; fuzzy control; manipulators; neurocontrollers; parameter estimation; radial basis function networks; variable structure systems; Kalman filter; chattering effect elimination; fuzzy based sliding mode control; fuzzy controller design; fuzzy techniques; model disturbances; model parameter estimation; model variation; online RBF network; radial basis function networks; sequential training algorithm; two degree of freedom robot manipulator; Joints; Manipulators; Mathematical model; Radial basis function networks; Sliding mode control; Vectors; Fuzzy control; Kalman filter; Radial basis function; Robot manipulator; Sliding mode;

fLanguage

English

Publisher

ieee

Conference_Titel

Sciences of Electronics, Technologies of Information and Telecommunications (SETIT), 2012 6th International Conference on

Conference_Location

Sousse

Print_ISBN

978-1-4673-1657-6

Type

conf

DOI

10.1109/SETIT.2012.6482033

Filename

6482033