This paper describes four methods for robot trajectory control. These methods are a standard PID controller, a Computed Torque Method (CTM), a neural networks based inverse controller and a neural network based Internal Model Controller(IMC). The IMC is investigated as an alternative to the basic inverse control scheme that is difficult to implement. The results presented show the superior ability of the proposed neural network based IMC scheme at adapting to changes in the dynamic parameters of the robot.