Disturbance Observer–Based Nonlinear Model Predictive Control for Air-Breathing Hypersonic Vehicles

Abstract

The disturbance-observer-based nonlinear model predictive control (DOB-NMPC) for air-breathing hypersonic vehicles (AHVs) is proposed in this paper. The longitudinal dynamic model of generic AHVs is first redesigned and optimized for prediction, whereas the cost function of nonlinear model predictive control (NMPC) is designed with series expansions and derivative feedback. A disturbance-observer-based control (DOBC) law is then developed for enhancing robustness in the presence of external disturbances and parameter uncertainties. The relationship among tracking errors, sample time, and estimation errors is finally investigated. Compared with existing tracking control for AHVs, the proposed DOB-NMPC achieves tracking commands effectively without sacrificing the nominal tracking performance, and the convergence range of tracking errors is verified by stability analysis and simulation studies.