An adaptive control algorithm based on the sliding mode principle, equipped with fuzzy logic to handle system modeling uncertainties, is developed in this paper. Along with a neural-network learning scheme that enhances the adaptive control capability, this controller performs satisfactory tracking control for a large class of robot models that contain significant but unknown friction and disturbances. Both mathematical analysis and computer simulation are enclosed for demonstration.
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