Robust Adaptive Control of Hypersonic Vehicle Considering Inlet Unstart

In this paper, a model reference adaptive control (MRAC) augmentation method of linear controller is proposed for air-breathing hypersonic vehicle (AHV) during inlet unstart. With the development flight technology, vehicles have been gradually moving to stage weaponization. During maneuvers, changes attitude, Mach number and back pressure can cause unstart phenomenon scramjet. Inlet causes significant in aerodynamics AHV, which may lead deterioration tracking performance or instability system. Therefore, we firstly establish considering unstart, caused by described as nonlinear uncertainty. Then, an MRAC radial basis function (RBF) neural network used schedule parameters MRAC. Furthermore, Lyapunov constructed prove stability method. Finally, numerical simulations show that compared with method, stabilize attitude more quickly after provides favorable conditions restart, thus verifying effectiveness paper.