Mohammed Salem; Mohamed F. Khelfi

Sequential Adaptive RBF-Fuzzy Variable Structure Control Applied to Robotics Systems

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Author(s)

Mohammed Salem ^1,* Mohamed F. Khelfi ²

1. University of Oran, Faculty of Exact and Applied Sciences, Oran, 31000, Algeria

2. University of Oran, Faculty of Exact and Applied Sciences, RIIR Lab, Oran, 31000, Algeria

* Corresponding author.

DOI: https://doi.org/10.5815/ijisa.2014.09.03

Received: 4 Sep. 2013 / Revised: 22 Jan. 2014 / Accepted: 15 Apr. 2014 / Published: 8 Aug. 2014

Index Terms

Radial Basis Function Networks, Sequential Training, Growing and Pruning, Fuzzy Control, Variable Structure Control, Robot Manipulator

Abstract

In this paper, we present a combination of sequential trained radial basis function networks and fuzzy techniques to enhance the variable structure controllers dedicated to robotics systems. In this aim, four RBFs networks were used to estimate the model based part parameters (Inertia, Centrifugal and Coriolis, Gravity and Friction matrices) of a variable structure controller so to respond to model variation and disturbances, a sequential online training algorithm based on Growing-Pruning "GAP" strategy and Kalman filter was implemented. To eliminate the chattering effect, the corrective control of the VS control was computed by a fuzzy controller. Simulations are carried out to control three degrees of freedom SCARA robot manipulator where the obtained results show good disturbance rejection and chattering elimination.

Cite This Paper

Mohammed Salem, Mohamed F. Khelfi, "Sequential Adaptive RBF-Fuzzy Variable Structure Control Applied to Robotics Systems", International Journal of Intelligent Systems and Applications(IJISA), vol.6, no.9, pp.19-29, 2014. DOI:10.5815/ijisa.2014.09.03

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International Journal of Intelligent Systems and Applications (IJISA)