International Journal of Intelligent Systems and Applications (IJISA)
IJISA Vol. 6, No. 11, 8 Oct. 2014
Cover page and Table of Contents: PDF (size: 659KB)
Sequential Adaptive Fuzzy Inference System Based Intelligent Control of Robot Manipulators
Full Text (PDF, 659KB), PP.49-56
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Author(s)
Sahraoui Mustapha
1,*
Khelfi Mohamed Faycal
1
Salem Mohammed
1
Index Terms
Artificial Intelligence, SAFIS (Sequential Adaptive Fuzzy Inference System), Neuro-Fuzzy Networks, Nonlinear System, Control, Robot Manipulator
Abstract
The present paper is dedicated to the presentation and implementation of an optimized technique allowing an on-line estimation of a robot manipulator parameters to use them in a computed torque control. Indeed the proposed control law needs the exact robot model to give good performances. The complexity of the robot manipulator and its strong non-linearity makes it hard to know its parameters. Therefore, we propose in this paper to use neuro-fuzzy networks Sequential Adaptive Fuzzy Inference System (SAFIS) to estimate the parameters of the controlled robot manipulator.
Cite This Paper
Sahraoui Mustapha, Khelfi Mohamed Fayçal, Salem Mohammed, "Sequential Adaptive Fuzzy Inference System Based Intelligent Control of Robot Manipulators", International Journal of Intelligent Systems and Applications(IJISA), vol.6, no.11, pp.49-56, 2014. DOI:10.5815/ijisa.2014.11.07
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