Nonlinear disturbance observer-based model predictive control for a generic hypersonic vehicle

Abstract

This article investigates a nonlinear disturbance observer-based model predictive control algorithm for the longitudinal dynamics of a generic hypersonic vehicle under external disturbances and system parameter perturbations. The model predictive control is combined with the nonlinear disturbance observer technique for uncertainty compensation. The nonlinear dynamics are first transformed into the linear structure with state-dependent coefficient matrices. At each sampling instant, the internal state-space model for prediction is obtained through a normal discretization procedure. Based upon this model, the model predictive controller is designed in nominal condition. Finally, a nonlinear disturbance observer is presented to estimate the uncertainty and a disturbance compensation gain is designed to compensate the uncertainty. Particularly, the offset-free tracking feature of the output for the reference signal is proved. Simulations show that the controls and the states are all in their given constraint scopes, and velocity and altitude track the reference signals accurately in steady state even under mismatched disturbances. Compared with pure model predictive control, the proposed method provides stronger robustness against various perturbations.