Dynamic surface control for nonlinear hypersonic air vehicle using neural network

In this paper dynamic surface control (DSC) technique is combined with neural network based adaptive control design framework to design the longitudinal dynamics controller for a nonlinear generic hypersonic air vehicle (HSAV). Detailed stability analysis is carried out to prove the uniform ultimate boundedness of all the signals in the closed loop system. The effectiveness of the proposed strategy is demonstrated by simulation of the longitudinal model of the HSAV for trimmed cruise conditions of 110,000 ft and Mach 15 where the responses of the vehicle to a step change in altitude and airspeed are evaluated.