Considering the external disturbances and the control input saturation constraint problems existing in the trajectory tracking control of the robot manipulators, an antiwindup neural network dynamic surface control algorithm was proposed.Whereas the terms of the model uncertainties and the external disturbances could be compensated by the radial basis function neural networks, and the saturation constraint problem could be solved by bringing into an auxiliary antiwindup function, the integral control law was obtained by the dynamic surface control law.The designed control law can solve the phenomenon of “differential explosion” existing in the traditional backstepping control, avoiding the chattering phenomenon appearing in the sliding mode control, and the robustness constraint existing in traditional adaptive control. Finally, relevant Lyapunov function was designed to validate the semiglobally gradually stability of the closed loop system, and the simulation results further verified the credibility of the proposed controller.