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

Article type: Research Article

Authors: de Jesús Rubio, José^{; *} | Garcia, Enrique | Ochoa, Genaro | Elias, Israel | Cruz, David Ricardo | Balcazar, Ricardo | Lopez, Jesus | Novoa, Juan Francisco

Affiliations: Sección de Estudios de Posgrado e Investigación, ESIME Azcapotzalco, Instituto Politécnico Nacional, Col. Santa Catarina, México D.F., México

Correspondence: [*] Corresponding author. José de Jesús Rubio, Sección de Estudios de Posgrado e Investigación, ESIME Azcapotzalco, Instituto Politécnico Nacional, Av. de las Granjas no. 682, Col. Santa Catarina, México D.F., 02250, México. E-mail: [email protected].

Abstract:  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.

Keywords: Unscented Kalman filter, greenhouse, solar dryer, experimental learning

DOI: 10.3233/JIFS-190216

Journal: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 5, pp. 6731-6741, 2019