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. © 2011. The authors-Published by Atlantis Press.
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Barragan, A., Márquez, J. M. A., Torres, M. J. A., Avello, A. J., & Al-Hadithi, B. M. (2011). Methodology for adapting the parameters of a fuzzy system using the extended kalman filter. In Proceedings of the 7th Conference of the European Society for Fuzzy Logic and Technology, EUSFLAT 2011 and French Days on Fuzzy Logic and Applications, LFA 2011 (Vol. 1, pp. 686–690). https://doi.org/10.2991/eusflat.2011.65
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