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Descripción
In this chapter the application of extended Kalman filter (EKF) for the parametric adaptation of a TS fuzzy model is presented, which allows obtaining accuratemodels without renounce the computational efficiency that characterizes the Kalman filter, and allows its implementation online with the process. It is also proposed two algorithms to adjust the antecedents and consequents of a TS fuzzy model, and have been presented several examples. Acknowledgments The authors would like to thank the Spanish Ministry of Economy and Competitiveness for its support to this work through projects DPI2010-17123 and DPI2010-21247-C02- 01, the Regional Government of Andalusia (Spain) for supporting TEP-6124 project, as well as the European Union Regional Development for funding the last two projects.
Internacional	Si
DOI	DOI: 10.2991/978-94-6239-082-9
Edición del Libro
Editorial del Libro	Atlantis (Atlantis Computational Intelligence Systems )
ISBN	978-94-6239-082-9
Serie	Atlantis (Atlantis Computational Intelligence Systems )
Título del Libro	Fuzzy Modeling and Control: Theory and Applications
Desde página	27
Hasta página	46

Esta actividad pertenece a memorias de investigación

• Autor: José Manuel Andújar
• Autor: Antonio Javier Barragán
• Autor: Basil Mohammed Al-Hadithi Abdul Qadir (UPM)
• Autor: Fernando Matia Espada (UPM)
• Autor: Agustin Jimenez Avello (UPM)

• Creador: Grupo de Investigación: Control Inteligente
• Centro o Instituto I+D+i: Centro de Automática y Robótica (CAR). Centro Mixto UPM-CSIC
• Departamento: Ingeniería Eléctrica, Electrónica Automática y Física Aplicada
• Departamento: Automática, Ingeniería Eléctrica y Electrónica e Informática Industrial