A method for estimating dynamic model parameters from flight data with unknown time skews is described and demonstrated. The method combines data reconstruction, nonlinear optimization, and equation-error parameter estimation in the frequency domain to accurately estimate both dynamic model parameters and the relative time skews in the data. Data from a nonlinear F-16 aircraft simulation with realistic noise, instrumentation errors, and arbitrary time skews were used to demonstrate the approach. The approach was further evaluated using flight data from a subscale jet transport aircraft, where the measured data were known to have relative time skews. Comparison of modeling results obtained from time-skewed and time-synchronized data showed that the method accurately estimates both dynamic model parameters and relative time skew parameters from flight data with unknown time skews.


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    Titel :

    Dynamic Modeling from Flight Data with Unknown Time Skews


    Beteiligte:

    Kongress:

    2016 AIAA SciTech Forum and Exposition ; 2016 ; San Diego, CA, United States


    Erscheinungsdatum :

    2016-01-04


    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Keine Angabe


    Sprache :

    Englisch




    Dynamic Modeling from Flight Data with Unknown Time Skews

    Eugene A Morelli | Online Contents | 2017




    Dynamic Modeling from Flight Data with Unknown Time Skews

    Eugene A Morelli | Online Contents | 2017


    Dynamic Modeling from Flight Data with Unknown Time Skews

    Eugene A Morelli | Online Contents | 2017