This paper deals with the trajectory tracking control problem for electrically driven redundant robot manipulators. By combining actuator dynamics with manipulator's kinematics and dynamics, a novel control scheme is proposed for the electromechanical system. In this electromechanical system, the controller is designed at the dynamic level as well as at the actuator level. In the proposed control scheme, uncertain non-linear mechanical dynamics is approximated with the model-based controller combined with the model-free radial basis function neural network based controller together with adaptive bound. The behaviour of the uncertain electrical dynamics is approximated with the help of a radial basis function neural network. The designed controller achieves both the trajectory tracking and the subtask tracking effectively. Additionally, the designed control scheme controls the direct current motors being used to provide the desired currents and torques. The errors are shown to be asymptotically converging and the control scheme is shown to be stable using Lyapunov stability theory. Finally, the simulation results are produced for the rigid link electrically driven redundant robot manipulators to show the effectiveness of the proposed control scheme.