On-line Nonparametric Regression to learn State-Dependent Disturbances

Bas J. de Kruif, Theo J.A. de Vries

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    Abstract

    A combination of recursive least squares and weighted least squares is made which can adapt its structure such that a relation between in- and output can he approximated, even when the structure of this relation is unknown beforehand. This method can adapt its structure on-line while it preserves information offered by previous samples, making it applicable in a control setting. This method has been tested with compntergenerated data, and it b used in a simulation to learn the non-linear state-dependent effects, both with good success.
    Original languageEnglish
    Title of host publicationProceedings of the 2003 IEEE International Symposium on Intelligent Control (ISIC)
    Place of PublicationPiscataway, NJ
    PublisherOmniPress
    Pages75-80
    Number of pages5
    ISBN (Print)0-7803-7892-X, 0-7803-7891-1
    DOIs
    Publication statusPublished - 5 Oct 2003
    Event2003 IEEE International Symposium on Intelligent Control, ISIC 2003 - Houston, United States
    Duration: 5 Oct 20038 Oct 2003

    Publication series

    NameProceedings of the IEEE International Symposium on Intelligent Control
    PublisherIEEE
    Volume2003
    ISSN (Print)2158-9860

    Conference

    Conference2003 IEEE International Symposium on Intelligent Control, ISIC 2003
    Abbreviated titleISIC
    Country/TerritoryUnited States
    CityHouston
    Period5/10/038/10/03

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