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.


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    Titel :

    Data-Driven Model Development for the SuperSonic SemiSpan Transport


    Beteiligte:

    Erschienen in:

    AIAA Journal ; 51 , 6 ; 1333-1341


    Erscheinungsdatum :

    01.06.2013




    Medientyp :

    Aufsatz (Konferenz) , Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch