Two algorithms for the combined state and parameter estimation (CSPE) of a linear, time-invariant system are presented. Retrospective cost subsystem estimation is formulated under the assumption that the initial state is known. A smoother algorithm based on this formulation is developed for the case in which the initial state is unknown. It is numerically demonstrated that these algorithms are more accurate for CSPE than the extended Kalman filter and the unscented Kalman filter.


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    Titel :

    Retrospective Cost Subsystem Estimation and Smoothing for Linear Systems with Structured Uncertainty


    Beteiligte:

    Erschienen in:

    Erscheinungsdatum :

    2018-09-06


    Format / Umfang :

    19 pages




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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