The state-dependent Riccati equation-based estimator is becoming a popular estimation tool for nonlinear systems since it does not use system linearization. In this paper, the state-dependent Riccati equation-based estimator is compared with the widely used extended Kalman filter for three simple examples that appear in the open literature. It is demonstrated that, by simulation, the state-dependent Riccati equation-based estimator at best has comparable results to the extended Kalman filter but is often worse than the extended Kalman filter. In some cases, the state-dependent Riccati equation-based estimator does not converge, even though the system considered satisfies all the mathematical constraints on controllability and observability. Sufficient detail is presented in the paper so that the interested reader cannot only duplicate the results but perhaps make suggestions on how to get the state-dependent Riccati equation-based estimator to perform better.


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    Titel :

    Comparisons Between the Extended Kalman Filter and the State-Dependent Riccati Estimator


    Beteiligte:
    Berman, Andrew (Autor:in) / Zarchan, Paul (Autor:in) / Lewis, Brian (Autor:in)

    Erschienen in:

    Erscheinungsdatum :

    2014-05-12


    Format / Umfang :

    12 pages




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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