Identification of a class of nonlinear state-space models using RPE techniques

W. W. Zhou, Mogens Blanke

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    The recursive prediction error methods in state-space form have been efficiently used as parameter identifiers for linear systems, and especially Ljung's innovations filter using a Newton search direction has proved to be quite ideal. In this paper, the RPE method in state-space form is developed to the nonlinear case and extended to include the exact form of a nonlinearity, thus enabling structure preservation for certain classes of nonlinear systems. Both the discrete and the continuous-discrete versions of the algorithm in an innovations model are investigated, and a nonlinear simulation example shows a quite convincing performance of the filter as combined parameter and state estimator.
    Original languageEnglish
    Title of host publication25th IEEE Conference on Decision and Control
    VolumeVolume 25
    Publication date1986
    Publication statusPublished - 1986
    Event25th IEEE Conference on Decision and Control - Athens, Greece
    Duration: 10 Dec 198612 Dec 1986
    Conference number: 25


    Conference25th IEEE Conference on Decision and Control

    Bibliographical note

    Copyright: 1986 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE


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