Conference paper · Journal article
Artificial Neural Network Based State Estimators Integrated into Kalmtool
Department of Electrical Engineering, Technical University of Denmark1
Automation and Control, Department of Electrical Engineering, Technical University of Denmark2
Department of Informatics and Mathematical Modeling, Technical University of Denmark3
Mathematical Statistics, Department of Informatics and Mathematical Modeling, Technical University of Denmark4
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.
Language: | English |
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Publisher: | International Federation of Automatic Control |
Year: | 2012 |
Pages: | 1547-1552 |
Proceedings: | 16th IFAC Symposium on System Identification |
Series: | Ifac Proceedings Volumes (ifac-papersonline) |
ISBN: | 3902823062 and 9783902823069 |
ISSN: | 14746670 |
Types: | Conference paper and Journal article |
DOI: | 10.3182/20120711-3-BE-2027.00303 |
ORCIDs: | Ravn, Ole and Poulsen, Niels Kjølstad |