The availability of suitable methods for system identification from flight data of rotorcraft flight mechanics models is one of the critical issues to enhance the competitiveness of the rotorcraft industry. In fact, system identification permits to reduce the time to market, costs and risks in the development process of new products. In this paper a new hybrid time-frequency approach for rotorcraft system identification is proposed. The identification process is performed in the framework of a multi-step strategy and a specific methodology has been selected to comply with each step objective. The use of a hybrid time-frequency approach allows to exploit the advantage of both time and frequency identification techniques and to obtain an identified model suitable in the whole frequency range of interest (from low to high frequency). Furthermore the multi-step strategy decomposes the complex starting problem in simplified sub-problems. The proposed methodology has been applied to simulated data of the UH60 Black Hawk, generated using the FLIGHTLAB multi-body simulation environment. The reported results demonstrate the effectiveness of the proposed technique in terms of convergence and capability of extracting from flight data relevant information on the vehicle dynamic behaviour.


    Access

    Access via TIB

    Check availability in my library


    Export, share and cite



    Title :

    A hybrid time and frequency method for rotorcraft model identification from flight data


    Additional title:

    Eine hybride Zeit-Frequenz-Methode für die Drehflügler-Modellidentifikation aus Flugdaten


    Contributors:
    Vitale, A. (author) / Genito, N. (author) / Federico, L. (author) / Filippone, E. (author) / Ciniglio, U. (author) / Corraro, F. (author)


    Publication date :

    2010


    Size :

    8 Seiten, 14 Quellen


    Type of media :

    Conference paper


    Type of material :

    Print


    Language :

    English




    Hybrid Approach for Rotorcraft Identification from Flight Data

    Corraro, F. / Federico, L. / Genito, N. et al. | British Library Conference Proceedings | 2011



    Rotorcraft Parameter Identification from Real Time Flight Data

    Kumar, Rajan / Ganguli, Ranjan / Omkar, S. N. et al. | AIAA | 2008


    Identification of Linear Time-Periodic Systems from Rotorcraft Flight-Test Data

    Saetti, Umberto / Horn, Joseph F. / Berger, Tom et al. | AIAA | 2019