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.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

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


    Contributors:

    Published in:

    Publication date :

    2014-09-01




    Type of media :

    Conference paper , Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English





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

    Berman, Andrew / Zarchan, Paul / Lewis, Brian | AIAA | 2013


    Comparisons Between the Extended Kalman Filter and the State-Dependent Riccati Estimator (AIAA 2013-4868)

    Berman, A. / Zarchan, P. / Lewis, B. et al. | British Library Conference Proceedings | 2013


    State-Dependent Riccati Equation Filter

    Zarchan, Paul / Musoff, Howard | AIAA | 2015


    Data-driven State-of-Charge estimator for electric vehicles battery using robust extended Kalman filter

    Xiong, R. / Sun, F. C. / He, H. W. | British Library Online Contents | 2014