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    Iterative Model Construction Methods for Multivariable State-Space Identification

    Iterative Model Construction Methods for Multivariable State-Space Identification


    When applied in aerospace engineering, the object of system identification is to estimate stability and control derivatives. These coefficients are the elements of the state matrix and input matrix in the state space equation that describes the dynamical behavior of the aircraft. The parameters are estimated using flight data that is recorded during special flight tests. Mainly due to the presence of the rotor, helicopters have to be treated differently than fixed wing aircraft. This leads to special approaches for the identification of rotary wing aircraft. A working group of NATO's Advisory Group on Aerospace Research and Development (AGARD) has investigated many of these procedures. The procedure that is followed here is based on frequency domain methods, since these techniques have several advantages for the identification of helicopters. The objectives of the TUD/NLR project are both the development of algorithms based on this approach and the application to flight data.

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    Titel :

    Iterative Model Construction Methods for Multivariable State-Space Identification

    Beteiligte:
    M. W. Soijer (Autor:in) / J. A. Mulder (Autor:in) / J. H. Breeman (Autor:in)
    Erscheinungsdatum :

    1996

    Format / Umfang :

    178 pages

    Medientyp :

    Report

    Format :

    Keine Angabe

    Sprache :

    Englisch

    Schlagwörter :

    Control Systems & Control Theory , Space Technology , Aircraft , Iterative models , Multivariable , Construction methods , Algorithms , Flight data , Foreign technology , State-space identification , Frequency domain methods

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