An integrated methodology for rotorcraft system identification consists of rotorcraft mathematical modeling, three distinct data processing steps, and a technique for designing inputs to improve the identifiability of the data. These elements are as follows: (1) a Kalman filter smoother algorithm which estimates states and sensor errors from error corrupted data. Gust time histories and statistics may also be estimated; (2) a model structure estimation algorithm for isolating a model which adequately explains the data; (3) a maximum likelihood algorithm for estimating the parameters and estimates for the variance of these estimates; and (4) an input design algorithm, based on a maximum likelihood approach, which provides inputs to improve the accuracy of parameter estimates. Each step is discussed with examples to both flight and simulated data cases.


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    Titel :

    Development of advanced techniques for rotorcraft state estimation and parameter identification


    Beteiligte:
    Hall, W. E., Jr. (Autor:in) / Bohn, J. G. (Autor:in) / Vincent, J. H. (Autor:in)

    Erscheinungsdatum :

    01.11.1980


    Medientyp :

    Report


    Format :

    Keine Angabe


    Sprache :

    Englisch




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