Multiple model predictive control for large envelope flight of hypersonic vehicle systems

Considering the strong nonlinearity, wide flight envelope and hard constraints of hypersonic vehicle (HV), we present a multiple model predictive control (MMPC) strategy for the control of HV's large envelope flight. Firstly, we divide the flight envelope of HV into several sub-regions based on gap metric theory. A novel algorithm is then developed to determine the approximated linear model for each sub-region. On this basis, model predictive control with infinite horizon cost is applied to design the sub-region controllers. To guarantee the stability of closed-loop system, we propose a multi-model switching strategy based on dynamic pressure. At last, the tracking performance of MMPC is verified on the hardware in the loop simulation (HLPS) platform dSPACE.