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.
large envelope flight hv gap metric dspace multi-model predictive control