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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    Title :

    Optimal Partitioned State Kalman Estimator


    Contributors:
    Karsaz, A (author) / Khaloozadeh, H (author) / Darbandi, M (author)


    Publication date :

    2010-06-01


    Size :

    536786 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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