Unscented Kalman filter for learning of a solar dryer and a greenhouse

José De Jesús Rubio; Enrique Garcia; Genaro Ochoa; Israel Elias; David Ricardo Cruz; Ricardo Balcazar; Jesus Lopez; Juan Francisco Novoa

doi:10.3233/JIFS-190216

Unscented Kalman filter for learning of a solar dryer and a greenhouse

José De Jesús Rubio, Enrique Garcia, Genaro Ochoa, Israel Elias, David Ricardo Cruz, Ricardo Balcazar, Jesus Lopez, Juan Francisco Novoa

Escuela Superior de Ingeniería Mecánica y Eléctrica (ESIME), Unidad Azcapotzalco

Producción científica: Contribución a una revista › Artículo › revisión exhaustiva

16 Citas (Scopus)

Resumen

An unscented Kalman filter can be applied for the experimental learning of the solar dryer for oranges drying and the greenhouse for crop growth to know better the processes and to improve their performances. The contributions of this document are: a) an unscented Kalman filter is designed for the learning of nonlinear functions, b) the unscented Kalman filter is applied for the experimental learning of the two mentioned processes.

Idioma original	Inglés
Páginas (desde-hasta)	6731-6741
Número de páginas	11
Publicación	Journal of Intelligent and Fuzzy Systems
Volumen	37
N.º	5
DOI	https://doi.org/10.3233/JIFS-190216
Estado	Publicada - 2019

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AU - De Jesús Rubio, José

AU - Garcia, Enrique

AU - Ochoa, Genaro

AU - Elias, Israel

AU - Cruz, David Ricardo

AU - Balcazar, Ricardo

AU - Lopez, Jesus

AU - Novoa, Juan Francisco

PY - 2019

Y1 - 2019

N2 - An unscented Kalman filter can be applied for the experimental learning of the solar dryer for oranges drying and the greenhouse for crop growth to know better the processes and to improve their performances. The contributions of this document are: a) an unscented Kalman filter is designed for the learning of nonlinear functions, b) the unscented Kalman filter is applied for the experimental learning of the two mentioned processes.

AB - An unscented Kalman filter can be applied for the experimental learning of the solar dryer for oranges drying and the greenhouse for crop growth to know better the processes and to improve their performances. The contributions of this document are: a) an unscented Kalman filter is designed for the learning of nonlinear functions, b) the unscented Kalman filter is applied for the experimental learning of the two mentioned processes.

KW - Unscented Kalman filter

KW - experimental learning

KW - greenhouse

KW - solar dryer

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ER -

Unscented Kalman filter for learning of a solar dryer and a greenhouse

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