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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    Title :

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


    Contributors:

    Publication date :

    2016


    Size :

    22 pages


    Type of media :

    Report


    Type of material :

    No indication


    Language :

    English






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