Design of adaptive sliding mode controller for missiles based on neural networks

Based on the nonlinear six degree-of-freedom missile model, the missile system was separated into four loops according to time-scale separation principle. Taking account of the fast and slow loops, an adaptive sliding mode controller based on the neural networks was proposed. Firstly, the nonlinear system was decoupled according to feedback linearization in both of the fast and slow loops. And then the adaptive sliding mode controller based on neural networks was designed to guarantee robustness and performance, in which the neural network was used to learn the system uncertainties adaptively. Both of the theoretical analysis and computer simulations indicate that not only the robustness of the controller is great, but also the stability of the closed-loop system is guaranteed.