An optimal reduced-order observer-estimator (filter) is developed which can provide a full-dimensional vector of state estimates for systems where the dimension of the measurement vector is smaller than that of the state vector and none of the measurements are noise free. The reduced-order filter consists of two subfilters each of which provides a subset of the optimal estimate. A two-step L-K transformation is employed to minimize the estimate error variance of each subfilter. The optimal reduced-order filter developed is computationally efficient.<>


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    An optimal reduced-order stochastic observer-estimator


    Contributors:
    Hong, L. (author)


    Publication date :

    1992-04-01


    Size :

    434691 byte




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English



    Optimal reduced-order observer-estimators

    HADDAD, WASSIM M. / BERNSTEIN, DENNIS S. | AIAA | 1990


    Optimal reduced-order observer-estimators

    HADDAD, WASSIM / BERNSTEIN, DENNIS | AIAA | 1989




    Fuzzy ellipsoidal state observer of reduced order

    Kussul, N.N. | Tema Archive | 2000