Artificial Neural Network Based State Estimators Integrated into Kalmtool

Publication: Research - peer-reviewArticle in proceedings – Annual report year: 2012

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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
StatePublished

Conference

Conference16th IFAC Symposium on System Identification
CountryBelgium
CityBrussels
Period11/07/1213/07/12
Internet addresshttp://www.sysid2012.org/
NameIFAC Proceedings Volumes (IFAC-PapersOnline)

Bibliographical note

Invited paper.

CitationsWeb of Science® Times Cited: No match on DOI

Keywords

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