Robust adaptive Dynamic Surface Control of a hypersonic flight vehicle

Abstract

A Dynamic Surface Control (DSC) technique combined with Neural Network adaptive framework is presented, to design a robust longitudinal dynamics controller for a generic nonlinear air-breathing hypersonic flight vehicle (AHFV) model. The dynamic model of the AHFV is transformed into a pure feedback form with uncertainties included in the formulation. A detailed stability analysis is carried out to prove that all the signals of the closed loop system are uniformly ultimately bounded. The robustness and performance of the designed controller is validated through numerical simulation of the AHFV model for trimmed cruise condition of 110,000 ft and Mach 15, in which the responses of the vehicle to a step change in air speed and altitude are analyzed for nominal and worst case parameter uncertainties.