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
- 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/).
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 (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 -