الفهرس 
Organization of the thesisOnly 14 pages are availabe for public view
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Abstract
Robot manipulators control systems are becoming increasingly important in research and industry as they present many interesting features and potentialities. Control of robot manipulators is a challenging problem which has attracted much attention in the control community. The main challenge in the motion control problem of rigid robot manipulators (RRMs) is the complexity of their dynamics and uncertainties. In recent decades, much effort has been devoted to this area and diverse results have been obtained In this thesis, two adaptive neuro-fuzzy inference system-based continuous sliding mode control systems are proposed for robust adaptive trajectory tracking control of RRMs with uncertain unknown dynamics and external disturbances. These adopted control approaches combine the proportional-integral-derivative (PID) controller, the continuous sliding mode control (CSMC) strategy and the adaptive control scheme and adaptive neuro-fuzzy inference system (ANFIS) control method so that they have not only the advantages of the sliding mode control but also the good performance of the neuro-fuzzy control approach. The theoretical domain in which controllers are designed can be divided into joint space-based and task space-based controllers.