Neural network high-order sliding mode control for a flexible air-breathing hypersonic flight vehicle

A nonlinear controller is exploited and analyzed for a generic flexible Hypersonic Vehicle longitudinal dynamics in this paper. A combined High-Order Sliding Mode technique and neural network is adopted for designing a dynamic state-feedback controller, providing stable tracking of velocity and altitude reference trajectories. The stability analysis of the closed-loop system and the convergence of system outputs are verified based on the Lyapunov theorem. Numerical simulation results from the flexible Hypersonic Vehicle model demonstrate the effectiveness of the proposed control scheme.