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.


    Access

    Access via TIB

    Check availability in my library


    Export, share and cite



    Title :

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


    Contributors:

    Conference:

    2016 AIAA SciTech Conference ; 2016 ; San Diego, CA, United States


    Publication date :

    2016-01-04


    Type of media :

    Conference paper


    Type of material :

    No indication


    Language :

    English