To solve the problem of low firing accuracy of shipborne artillery at sea, an optimal sliding mode control strategy based on RBF neural network is proposed.Firstly, the mathematic model of shipborne artillery servo system is established, and a Global Robust Optimal Sliding Mode Controller (GROSMC) is designed based on the linear quadratic optimal control theory and sliding mode control.This improves the response speed and ensures the good robustness of the system.Then, RBF neural network is used to dynamically adjust the gain of the switching control item to reduce the sliding mode chattering problem.Finally, the effectiveness of the designed controller is verified by simulation comparison.The simulation results show that this strategy has good control performance and meets the system requirements.