Proceedings of the 7th conference of the European Society for Fuzzy Logic and Technology (EUSFLAT-11)

Methodology for adapting the parameters of a fuzzy system using the extended Kalman filter

Authors
Antonio Javier Barragán Piña, José Manuel Andújar Márquez, Mariano J. Aznar Torres, Agustín Jiménez Avello, Basil M. Al-Hadithi
Corresponding Author
Antonio Javier Barragán Piña
Available Online August 2011.
DOI
https://doi.org/10.2991/eusflat.2011.65How to use a DOI?
Keywords
Kalman filter, estimation, fuzzy system, modeling.
Abstract
When we try to analyze and to control a system whose model was obtained only based on input/output data, accuracy is essential in the model. On the other hand, to make the procedure practical, the modeling stage must be computationally efficient. In this regard, this paper presents the application of extended Kalman filter for the parametric adaptation of a fuzzy model.
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This is an open access article distributed under the CC BY-NC license.

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Proceedings
Proceedings of the 7th conference of the European Society for Fuzzy Logic and Technology
Part of series
Advances in Intelligent Systems Research
Publication Date
August 2011
ISBN
978-90-78677-00-0
ISSN
1951-6851
DOI
https://doi.org/10.2991/eusflat.2011.65How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - CONF
AU  - Antonio Javier Barragán Piña
AU  - José Manuel Andújar Márquez
AU  - Mariano J. Aznar Torres
AU  - Agustín Jiménez Avello
AU  - Basil M. Al-Hadithi
PY  - 2011/08
DA  - 2011/08
TI  - Methodology for adapting the parameters of a fuzzy system using the extended Kalman filter
BT  - Proceedings of the 7th conference of the European Society for Fuzzy Logic and Technology
PB  - Atlantis Press
SP  - 686
EP  - 690
SN  - 1951-6851
UR  - https://doi.org/10.2991/eusflat.2011.65
DO  - https://doi.org/10.2991/eusflat.2011.65
ID  - Piña2011/08
ER  -