Abstarct: This thesis presents a novel two-level control approach for a robot manipulator that uses adaptive control as the first level control in order to achieve tracking goals and the robust fuzzy control to guarantee stability in the closed loop system as a supervisory controller. The main advantage of the supervisory control is using different controllers to access the accuracy and stability. Designing of controllers are free from dynamical model of the robot manipulator and also it is baxsed on voltage control strategy that is more efficient, simpler, and less computationally than torque control strategy. In this thesis, at first the adaptive and fuzzy controllers will be proposed and the structure of the supervisory control system will be introduced. Finally, the performance of the proposed control system is simulated by implementing on the articulated robot manipulator driven by permanent magnet dc motors. The simulation results show the efficient performance of the control system method.