Iterative-learning-based sliding mode control design for hypersonic vehicles with wind effects

A new sliding mode control method based on iterative learning is proposed for the longitudinal dynamics of hypersonic flight vehicles in the presence of wind effects. First, the wind effects are taken into the system by introducing the accessional attack angle, and with output-feedback transformation, the effects of the accessional attack angle and aerodynamic uncertainties are all modelled as lumped disturbances. Then, a novel sliding mode control scheme combined with command filtered technique is designed for the velocity subsystem and the altitude subsystem independently, while iterative learning laws are constructed to estimate the unknown disturbances. Furthermore, the stability and learning convergence of the system are rigorously proven via Lyapunov stability theory. By comparison, simulation results demonstrate that the presented strategy can efficiently achieve high tracking accuracy in spite of wind effects.