In addition to the influence of the vibration of ground vehicles in subgrade environment, the amphibious weapons will also be affected by the swinging of its carrier in marine environment, which may result in the deviation of the launch angle of the amphibious weapon launcher.By using the self-adaptation and self-learning ability of wavelet neural network, an internal model control method based on self-built wavelet neural network is proposed for the amphibious weapon servo system.The excitation strength and attenuation degree of the wavelet basis function are used to add neuron nodes, or to trim or delete neuron nodes to optimize the hidden layer structure, and then the LM algorithm is used to improve the learning rate.The self-built wavelet neural network is used to identify the forward and inverse models of the internal model control system to improve the control technology.The final results show that the method can effectively improve the systems anti-jamming capability, launching accuracy and adjustment speed.