Flight testing and modeling techniques were developed to accurately identify global nonlinear aerodynamic models for aircraft in real time. The techniques were developed and demonstrated during flight testing of a remotely-piloted subscale propeller-driven fixed-wing aircraft using flight test maneuvers designed to simulate a Learn-To-Fly scenario. Prediction testing was used to evaluate the quality of the global models identified in real time. The real-time global nonlinear aerodynamic modeling algorithm will be integrated and further tested with learning adaptive control and guidance for NASA Learn-To-Fly concept flight demonstrations.


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    Titel :

    Real-Time Global Nonlinear Aerodynamic Modeling for Learn-To-Fly


    Beteiligte:
    E. A. Morelli (Autor:in)

    Erscheinungsdatum :

    2016


    Format / Umfang :

    22 pages


    Medientyp :

    Report


    Format :

    Keine Angabe


    Sprache :

    Englisch






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