Data-Driven Model Development for the SuperSonic SemiSpan Transport

摘要

We investigate two common approaches to model development for robust control synthesis in the aerospace community; namely, reduced-order aeroservoelastic modeling based on structural finite-element and computational-fluid-dynamics-based aerodynamic models and a data-driven system-identification procedure. It is shown via analysis of experimental SuperSonic SemiSpan Transport wind-tunnel data that, using a system-identification approach, it is possible to estimate a model at a fixed Mach number that is parsimonious and robust across varying dynamic pressures while the numerical reduced-order model offers significantly less predicative capability.