Artificial Neural Network Based State Estimators Integrated into Kalmtool

    Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

    Abstract

    In this paper we present a toolbox enabling easy evaluation and comparison of dierent ltering algorithms. The toolbox is called Kalmtool and is a set of MATLAB tools for state estimation of nonlinear systems. The toolbox now contains functions for Articial Neural Network Based State Estimation as well as for DD1 lter and the DD2 lter, as well as functions for Unscented Kalman lters and several versions of particle lters. The toolbox requires MATLAB version 7, but no additional toolboxes are required.
    Original languageEnglish
    Title of host publicationSystem Identification
    Volume16
    PublisherInternational Federation of Automatic Control
    Publication date2012
    Pages1547-1552
    ISBN (Print)978-3-902823-06-9
    DOIs
    Publication statusPublished - 2012
    Event16th IFAC Symposium on System Identification - Square - Brussels Meeting Centre, Brussels, Belgium
    Duration: 11 Jul 201213 Jul 2012
    http://www.sysid2012.org/

    Conference

    Conference16th IFAC Symposium on System Identification
    LocationSquare - Brussels Meeting Centre
    Country/TerritoryBelgium
    CityBrussels
    Period11/07/201213/07/2012
    Internet address
    SeriesIFAC Proceedings Volumes (IFAC-PapersOnline)

    Bibliographical note

    Invited paper.

    Keywords

    • Simulation
    • Software tools
    • State estimation
    • Kalman ltering
    • Neural networks
    • Nonlinear systems

    Fingerprint

    Dive into the research topics of 'Artificial Neural Network Based State Estimators Integrated into Kalmtool'. Together they form a unique fingerprint.

    Cite this