Sequential Adaptive Fuzzy Inference System Based Intelligent Control of Robot Manipulators

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.

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