Abstract: A neural network control scheme is proposed for the control of robotic manipulator including actuator dynamics in this paper. In the proposed control scheme, the radial basis function (RBF) network is adopted to approximate the nonlinear dynamics of the robotic manipulator. In addition, a robust control is used to eliminate the neural network modelling error and disturbance. Uniformly ultimate boundedness (UUB) stability of the closed-loop system can be guaranteed by Lyapunov theory. Finally, a hardware-in-the-loop simulation technique based control system is developed. Furthermore, the proposed control scheme is applied to the same robotic manipulator together with PD control and adaptive control. Experiment results confirm the validity of the proposed control scheme by comparing it with other control strategies.