A sliding mode control strategy based on RBF neural network is proposed to solve the problem of low accuracy of ship borne weapons when firing at sea. According to the working principle of ship borne weapon servo system, the mathematical model of ship borne weapon servo system is established. By using the superiority of sliding mode in non-linear control, the perturbation parameters of the system are approximated adaptively by RBF neural network to solve the chattering problem caused by sliding mode switching, and control law of the ship borne weapon servo system position controller is obtained. The simulation results show that the control strategy can improve the fast response ability and dynamic accuracy of the ship borne weapon servo system, and meet the system requirements.