Application of the Extended Kalman filter to fuzzy modeling: Algorithms and practical implementation
- Antonio Javier Barragán Piña, José Manuel Andújar Márquez, Mariano J. Aznar Torres, Agustín Jiménez, Basil M Al-Hadithi
- Corresponding Author
- Antonio Javier Barragán Piña
Available Online August 2011.
- https://doi.org/10.2991/eusflat.2011.23How to use a DOI?
- Algorithm, Kalman filter, estimation, fuzzy system, modeling.
- Modeling phase is fundamental both in the analysis process of a dynamic system and the design of a control system. If this phase is in-line is even more critical and the only information of the system comes from input/output data. Some adaptation algorithms for fuzzy system based on extended Kalman filter are presented in this paper, which allows obtaining accurate models without renounce the computational efficiency that characterizes the Kalman filter, and allows its implementation in-line with the process.
- 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 AU - Basil M Al-Hadithi PY - 2011/08 DA - 2011/08 TI - Application of the Extended Kalman filter to fuzzy modeling: Algorithms and practical implementation BT - Proceedings of the 7th conference of the European Society for Fuzzy Logic and Technology PB - Atlantis Press SP - 691 EP - 698 SN - 1951-6851 UR - https://doi.org/10.2991/eusflat.2011.23 DO - https://doi.org/10.2991/eusflat.2011.23 ID - Piña2011/08 ER -