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

^*Corresponding author for this work

Ingeniería Electrónica y Automatización

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

1 Scopus citations

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.

Original language	English
Title of host publication	Proceedings of the 25th Autumn Meeting on Power, Electronics and Computing, ROPEC 2023
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9798350336887
DOIs	https://doi.org/10.1109/ROPEC58757.2023.10409358
State	Published - 2023
Event	25th Autumn Meeting on Power, Electronics and Computing, ROPEC 2023 - Ixtapa, Gro., Mexico Duration: 18 Oct 2023 → 20 Oct 2023

Publication series

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

Conference

Conference	25th Autumn Meeting on Power, Electronics and Computing, ROPEC 2023
Country/Territory	Mexico
City	Ixtapa, Gro.
Period	18/10/23 → 20/10/23

Access to Document

10.1109/ROPEC58757.2023.10409358

Cite this

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. In 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",

note = "Publisher Copyright: {\textcopyright} 2023 IEEE.; 25th Autumn Meeting on Power, Electronics and Computing, ROPEC 2023 ; Conference date: 18-10-2023 Through 20-10-2023",

year = "2023",

doi = "10.1109/ROPEC58757.2023.10409358",

language = "Ingl{\'e}s",

series = "Proceedings of the 25th Autumn Meeting on Power, Electronics and Computing, ROPEC 2023",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

booktitle = "Proceedings of the 25th Autumn Meeting on Power, Electronics and Computing, ROPEC 2023",

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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. in 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., Mexico, 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).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

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.

UR - https://www.scopus.com/pages/publications/85186140643

U2 - 10.1109/ROPEC58757.2023.10409358

DO - 10.1109/ROPEC58757.2023.10409358

M3 - Contribución a la conferencia

AN - SCOPUS:85186140643

T3 - Proceedings of the 25th Autumn Meeting on Power, Electronics and Computing, ROPEC 2023

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

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 25th Autumn Meeting on Power, Electronics and Computing, ROPEC 2023

Y2 - 18 October 2023 through 20 October 2023

ER -

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. In 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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