Optimization of the Model Predictive Control Parameters using Artificial Bee Colony Algorithm Applied to a Small-Scale Pasteurization Plant

Luis Caiza; Diego Benitez; Oscar Camacho

doi:10.1109/ROPEC58757.2023.10409358

Optimization of the Model Predictive Control Parameters using Artificial Bee Colony Algorithm Applied to a Small-Scale Pasteurization Plant

Luis Caiza, Diego Benitez, Oscar Camacho

Ingeniería Electrónica y Automatización

Producción científica: Capítulo del libro/informe/acta de congreso › Contribución a la conferencia › revisión exhaustiva

Resumen

This paper proposes a model predictive control (MPC) algorithm optimized using the artificial bee colony algorithm (ABC) to control the temperature of the pasteurization product in a small-scale pasteurization plant following a set point trajectory and minimizing power consumption. The proposed algorithm is compared with the MPC tuned by trial and error. The results show that the proposed ABC optimization-based MPC algorithm shows improvements in relation to trajectory tracking and disturbance rejection. A significant reduction in the integral squared error (ISE) of approximately 68.12% and in the settle times (up and down) of 58.90% and 84.40%, respectively, was achieved.

Idioma original	Inglés
Título de la publicación alojada	Proceedings of the 25th Autumn Meeting on Power, Electronics and Computing, ROPEC 2023
Editorial	Institute of Electrical and Electronics Engineers Inc.
ISBN (versión digital)	9798350336887
DOI	https://doi.org/10.1109/ROPEC58757.2023.10409358
Estado	Publicada - 2023
Evento	25th Autumn Meeting on Power, Electronics and Computing, ROPEC 2023 - Ixtapa, Gro., México Duración: 18 oct. 2023 → 20 oct. 2023

Serie de la publicación

Nombre	Proceedings of the 25th Autumn Meeting on Power, Electronics and Computing, ROPEC 2023

Conferencia

Conferencia	25th Autumn Meeting on Power, Electronics and Computing, ROPEC 2023
País/Territorio	México
Ciudad	Ixtapa, Gro.
Período	18/10/23 → 20/10/23

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10.1109/ROPEC58757.2023.10409358

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Caiza, L., Benitez, D., & Camacho, O. (2023). Optimization of the Model Predictive Control Parameters using Artificial Bee Colony Algorithm Applied to a Small-Scale Pasteurization Plant. En Proceedings of the 25th Autumn Meeting on Power, Electronics and Computing, ROPEC 2023 (Proceedings of the 25th Autumn Meeting on Power, Electronics and Computing, ROPEC 2023). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ROPEC58757.2023.10409358

Caiza, Luis ; Benitez, Diego ; Camacho, Oscar. / Optimization of the Model Predictive Control Parameters using Artificial Bee Colony Algorithm Applied to a Small-Scale Pasteurization Plant. Proceedings of the 25th Autumn Meeting on Power, Electronics and Computing, ROPEC 2023. Institute of Electrical and Electronics Engineers Inc., 2023. (Proceedings of the 25th Autumn Meeting on Power, Electronics and Computing, ROPEC 2023).

@inproceedings{81478cc8fafc4063b3f0625787f62138,

title = "Optimization of the Model Predictive Control Parameters using Artificial Bee Colony Algorithm Applied to a Small-Scale Pasteurization Plant",

abstract = "This paper proposes a model predictive control (MPC) algorithm optimized using the artificial bee colony algorithm (ABC) to control the temperature of the pasteurization product in a small-scale pasteurization plant following a set point trajectory and minimizing power consumption. The proposed algorithm is compared with the MPC tuned by trial and error. The results show that the proposed ABC optimization-based MPC algorithm shows improvements in relation to trajectory tracking and disturbance rejection. A significant reduction in the integral squared error (ISE) of approximately 68.12% and in the settle times (up and down) of 58.90% and 84.40%, respectively, was achieved.",

author = "Luis Caiza and Diego Benitez and Oscar Camacho",

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Caiza, L , Benitez, D & Camacho, O 2023, Optimization of the Model Predictive Control Parameters using Artificial Bee Colony Algorithm Applied to a Small-Scale Pasteurization Plant. En Proceedings of the 25th Autumn Meeting on Power, Electronics and Computing, ROPEC 2023. Proceedings of the 25th Autumn Meeting on Power, Electronics and Computing, ROPEC 2023, Institute of Electrical and Electronics Engineers Inc., 25th Autumn Meeting on Power, Electronics and Computing, ROPEC 2023, Ixtapa, Gro., México, 18/10/23. https://doi.org/10.1109/ROPEC58757.2023.10409358

Optimization of the Model Predictive Control Parameters using Artificial Bee Colony Algorithm Applied to a Small-Scale Pasteurization Plant. / Caiza, Luis ; Benitez, Diego ; Camacho, Oscar.
Proceedings of the 25th Autumn Meeting on Power, Electronics and Computing, ROPEC 2023. Institute of Electrical and Electronics Engineers Inc., 2023. (Proceedings of the 25th Autumn Meeting on Power, Electronics and Computing, ROPEC 2023).

Producción científica: Capítulo del libro/informe/acta de congreso › Contribución a la conferencia › revisión exhaustiva

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T1 - Optimization of the Model Predictive Control Parameters using Artificial Bee Colony Algorithm Applied to a Small-Scale Pasteurization Plant

AU - Caiza, Luis

AU - Benitez, Diego

AU - Camacho, Oscar

PY - 2023

Y1 - 2023

N2 - This paper proposes a model predictive control (MPC) algorithm optimized using the artificial bee colony algorithm (ABC) to control the temperature of the pasteurization product in a small-scale pasteurization plant following a set point trajectory and minimizing power consumption. The proposed algorithm is compared with the MPC tuned by trial and error. The results show that the proposed ABC optimization-based MPC algorithm shows improvements in relation to trajectory tracking and disturbance rejection. A significant reduction in the integral squared error (ISE) of approximately 68.12% and in the settle times (up and down) of 58.90% and 84.40%, respectively, was achieved.

AB - This paper proposes a model predictive control (MPC) algorithm optimized using the artificial bee colony algorithm (ABC) to control the temperature of the pasteurization product in a small-scale pasteurization plant following a set point trajectory and minimizing power consumption. The proposed algorithm is compared with the MPC tuned by trial and error. The results show that the proposed ABC optimization-based MPC algorithm shows improvements in relation to trajectory tracking and disturbance rejection. A significant reduction in the integral squared error (ISE) of approximately 68.12% and in the settle times (up and down) of 58.90% and 84.40%, respectively, was achieved.

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Caiza L , Benitez D , Camacho O. Optimization of the Model Predictive Control Parameters using Artificial Bee Colony Algorithm Applied to a Small-Scale Pasteurization Plant. En Proceedings of the 25th Autumn Meeting on Power, Electronics and Computing, ROPEC 2023. Institute of Electrical and Electronics Engineers Inc. 2023. (Proceedings of the 25th Autumn Meeting on Power, Electronics and Computing, ROPEC 2023). doi: 10.1109/ROPEC58757.2023.10409358

Optimization of the Model Predictive Control Parameters using Artificial Bee Colony Algorithm Applied to a Small-Scale Pasteurization Plant

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