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

DOI

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.

Copyright

© 2011, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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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 (EUSFLAT-11)
PB  - Atlantis Press
SP  - 686
EP  - 690
SN  - 1951-6851
UR  - https://doi.org/10.2991/eusflat.2011.65
DO  - 10.2991/eusflat.2011.65
ID  - Piña2011/08
ER  -