In view of the uncertainty and time-varying feature of internal parameters in the control of hydraulic servo system of large-caliber weapon, the traditional PID control is modified by taking the advantages of high robustness and fine fault-tolerant ability of the fuzzy control, while using the RBF neural network to solve the problem of poor accuracy of the fuzzy control.In addition, the ant colony clustering is used to initialize the initial parameters of the RBF neural network, and the conjugate gradient method is used for optimized training of the neural network.The simulation results show that, the control strategy can better suppress the time-varying and nonlinear problems of large-caliber weapon systems while ensuring the speed and accuracy of the system.