A new general two-stage algorithm was originally proposed to reduce the computational effort of the augmented state Kalman estimator. The conventional input estimation techniques assume constant input level and there are not covered a generalized input modeling. In this paper an innovative scheme is developed to overcome these drawbacks by using a new partitioned input dynamic modeling. In addition, authors propose a modified two-stage Kalman estimator with a new structure, which is an extension of the conventional input estimation techniques and is optimal for general, linear discrete-time systems.


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    Titel :

    Optimal Partitioned State Kalman Estimator


    Beteiligte:
    Karsaz, A (Autor:in) / Khaloozadeh, H (Autor:in) / Darbandi, M (Autor:in)


    Erscheinungsdatum :

    01.06.2010


    Format / Umfang :

    536786 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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