Online RBF and fuzzy based sliding mode control of robot manipulator

被引：0

作者：

Salem, Mohammed ^{[1
]}

Khelfi, Mohamed Faycal ^{[2
]}

机构：

[1] Mascara Univ, Fac Sci & Technol, RIIR Lab, Mascara, Algeria

[2] Univ Oran, Fac Sci, RIIR Lab, Oran, Algeria

来源：

2012 6TH INTERNATIONAL CONFERENCE ON SCIENCES OF ELECTRONICS, TECHNOLOGIES OF INFORMATION AND TELECOMMUNICATIONS (SETIT) | 2012年

关键词：

component; Fuzzy control; Kalman filter; Radial basis function; Robot manipulator; Sliding mode;

D O I：

暂无

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

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.

引用

页码：896 / 901

页数：6

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