In view of the uncertainty about the quad-rotor aerial vehicle system,a new control method is proposed by combining sliding mode control with the adaptive neural network.Considering the existing uncertainties in the actual system,such as inaccurate modeling and unknown parameters,and based on the sliding mode control,we constructed a RBF neural network to on-line approach the unknown functions of the system model,and designed an adaptive law to on-line estimate the weights of the neural network and the unknown parameters using the Lyapunov method.The stability of the system was verified by Lyapunov theorem.The simulation results show that:compared with the adaptive PID controller of the RBF neural network,this controller has a shorter settling time,less overshoot and better resistance to disturbances,and it also has a stronger robustness when the model parameters are changed.