Abstract
In this paper, a multivariable control using fuzzy logic and genetic algorithms (GA) is developed to control the incubation process of “gallus gallus domesticus” embryos. The incubation process is a system with high interactions among its input and output variables. A dynamic decoupling is used through Relative Gain Array (RGA) analysis to reduce these interactions. The proportional-integral (PI) controllers and the linear decoupler are designed from single-variable control structures obtained from a parametric identification for systems that can approximate first order and first order with a delay (FOPDT). Comparative performance analysis of PI, PI-Fuzzy, and PI-Fuzzy tuned with Genetic Algorithms controllers are evaluated using the integral squared error (ISE) and integral absolute error (IAE) through experimental tests using the NODEMCU ESP-WROOM-32 embedded system.
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This work was supported by the Universidad San Francisco de Quito through the Poli-Grants Program under Grant 17461.
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Balseca, A., Herrera, M., Camacho, O. (2023). Multivariable Control Approach Applied to the Embryo Incubation Process of Gallus Gallus Domesticus. In: Botto-Tobar, M., Zambrano Vizuete, M., Montes León, S., Torres-Carrión, P., Durakovic, B. (eds) Applied Technologies. ICAT 2022. Communications in Computer and Information Science, vol 1755. Springer, Cham. https://doi.org/10.1007/978-3-031-24985-3_12
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