OPTIMIZING BEER FERMENTATION THROUGH INTELLIGENT CONTROL

Authors

Azizbek Nodirbekovich Yusupbekov, Tashkent State Technical University. Address: 2 Universitet st., 100095, Tashkent city, Republic of Uzbekistan. E-mail: abek71@mail.ru;Follow
Mirjalol Yusupov, Tashkent State Technical University. Address: 2 Universitet st., 100095, Tashkent city, Republic of Uzbekistan. E-mail: yusupovmirjalolmm@gmail.com. Phone: +998942960111.Follow

Abstract

This paper presents an intelligent control approach for optimizing the beer fermentation process using fuzzy logic and adaptive neuro-fuzzy inference systems. By incorporating multivariable inputs—temperature error and pH deviation—the proposed system effectively handles the nonlinear dynamics and biological variability inherent in fermentation. Simulation results demonstrate improved control accuracy, responsiveness, and robustness compared to conventional methods, making the approach suitable for integration in modern brewery automation systems.

First Page

18

Last Page

23

References

1. Hornink, G. G. (2024). Principles of Beer Production and Enzymes in Mashing (2nd ed.). Alfenas-MG.
2. Yerolla, R., Nekkanti, S. H., Pullanikkattil, S., & Besta, C. S. (2023). Modeling and control of beer fermentation for optimal flavor and performance. Chemical Engineering & Technology, 46(8), 1554–1565. https://doi.org/10.1002/ceat.202200376
3. Wunderlich, S., & Back, W. (2009). Overview of manufacturing beer: Ingredients, processes, and quality criteria. In Beer in Health and Disease Prevention (pp. 3–16). Elsevier. https://doi.org/10.1016/B978-0-12-373891-2.00001-8
4. Zamudio Lara, J. M., Dewasme, L., Hernández Escoto, H., & Vande Wouwer, A. (2022). Parameter estimation of dynamic beer fermentation models. Foods, 11(22), 3602. https://doi.org/10.3390/foods11223602
5. Yusupbekov, A. N., & Yusupov, M. Sh. (2024). Development of a mathematical model for an intelligent process control system in brewing industry. Chemical Technology, Control and Management, 2024(5), 60–62. https://doi.org/10.59048/2181-1105.1630
6. Chai, W. Y., Teo, K. T. K., Tan, M. K., & Tham, H. J. (2022). Fermentation process control and optimization. Chemical Engineering & Technology, 45(10), 1731–1747. https://doi.org/10.1002/ceat.202200029
7. Eshbobaev, J., Norkobilov, A., Usmanov, K., Khamidov, B., Kodirov, O., & Avezov, T. (2024, September). Control of wastewater treatment processes using a fuzzy logic approach. In The 3rd International Electronic Conference on Processes (p. 39). MDPI. https://doi.org/10.3390/engproc2024067039
8. Jia, Y. (2021). Design of an intelligent greenhouse remote control system based on a fuzzy neural network. International Journal of Automation Technology, 15(2), 243–248. https://doi.org/10.20965/ijat.2021.p0243
9. Baqoyevich, M. G. (2023). Modeling and adjustment of a fuzzy controller in a bioreactor control system. Chemical Technology, Control and Management, 2023(2), 14–21. https://doi.org/10.59048/2181-1105.1439
10. Avazov, Y. S., & Abdullaeva, K. R. (2024). Implementation of the method of fuzzy control of the rectification process based on fuzzy logic. Chemical Technology, Control and Management, 2024(5), 193–199. https://doi.org/10.59048/2181-1105.1653
11. Eshbobaev, J. A., Khamidov, B. T., & Fallanza, M. T. (2025). Application of an adaptive neuro-fuzzy inference system to control the wastewater treatment process. Chemical Technology, Control and Management, 2025(1), 52–60. https://doi.org/10.59048/2181-1105.1654
12. Yusupbekov, N. R., Gulyamov, Sh. M., & Doshchanova, M. Yu. (2020). Neuro-fuzzy modeling for predictive control systems with complex technological processes and production. https://doi.org/10.34920/2020.1.73-83
13. Guerra, M. I. S., De Araújo, F. M. U., De Carvalho Neto, J. T., & Vieira, R. G. (2024). Survey on adaptive neural fuzzy inference system (ANFIS) architecture applied to photovoltaic systems. Energy Systems, 15(2), 505–541. https://doi.org/10.1007/s12667-022-00513-8
14. Tangarife Escobar, H. I., & Galvis Loaiza, O. M. (2020). Design and implementation of a fuzzy temperature control for a craft beer production microplant using PLC. Visión Electrónica, 14(2), 247–254. https://doi.org/10.14483/22484728.16178

Recommended Citation

Yusupbekov, Azizbek Nodirbekovich and Yusupov, Mirjalol (2025) "OPTIMIZING BEER FERMENTATION THROUGH INTELLIGENT CONTROL," Chemical Technology, Control and Management: Vol. 2025: Iss. 4, Article 2.
DOI: https://doi.org/10.59048/2181-1105.1693