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Ushbu maqolada bakteriyali oksidlash jarayonida qo‘llaniladigan bioreaktorning matematik modelini ishlab chiqish uchun yangi modellashtirish uslubiyati taklif etilgan. Adabiyotlar tahlili natijasiga ko‘ra, mavjud model bilan solishtirma tahlil o‘tkazildi. Bioreaktordagi parametrlarni rostlash uchun berilgan o‘rnatmalar asosida noravshan PID-rostlagichining koeffitsiyentlari sozlandi. Adabiyotlarda keltirilgan rostlagichlarni sozlash usullari solishtirma tahlil qilinganda, taklif etilayotgan uslubning samaradorligi isbotlandi. Tadqiqot natijasi shuni ko‘rsatadiki, taklif etilayotgan usul bioreaktordagi parametrlarni oqilona rostlashda yuqori unumdorlikka ega. Bundan tashqari, taklif etilayotgan usul o‘lchash jarayonida shovqinlar mavjud bo‘lgan holat uchun bioreaktor modelining nochiziqli holatida tekshirildi.

  • Ссылка в интернете
  • DOI
  • Дата создание в систему UzSCI 16-10-2024
  • Количество прочтений 36
  • Дата публикации 22-04-2024
  • Язык статьиO'zbek
  • Страницы61-71
Ўзбек

Ushbu maqolada bakteriyali oksidlash jarayonida qo‘llaniladigan bioreaktorning matematik modelini ishlab chiqish uchun yangi modellashtirish uslubiyati taklif etilgan. Adabiyotlar tahlili natijasiga ko‘ra, mavjud model bilan solishtirma tahlil o‘tkazildi. Bioreaktordagi parametrlarni rostlash uchun berilgan o‘rnatmalar asosida noravshan PID-rostlagichining koeffitsiyentlari sozlandi. Adabiyotlarda keltirilgan rostlagichlarni sozlash usullari solishtirma tahlil qilinganda, taklif etilayotgan uslubning samaradorligi isbotlandi. Tadqiqot natijasi shuni ko‘rsatadiki, taklif etilayotgan usul bioreaktordagi parametrlarni oqilona rostlashda yuqori unumdorlikka ega. Bundan tashqari, taklif etilayotgan usul o‘lchash jarayonida shovqinlar mavjud bo‘lgan holat uchun bioreaktor modelining nochiziqli holatida tekshirildi.

Русский

В данной статье представлена новая методология моделирования для разработки математической модели биореактора, используемого в процессе бактериального окисления. В результате изучения соответствующей литературы был проведён сравнительный анализ с существующей моделью. Для настройки параметров в биореакторе коэффициенты нечёткого ПИД-регулятора настраивались исходя из заданных настроек. Эффективность предложенного метода доказана при сравнении способов настройки регуляторов, представленных в литературе. Результаты исследования показывают, что предлагаемый способ обладает высокой эффективностью при рациональном регулировании параметров биореактора. Кроме того, предложенный метод был протестирован в нелинейном состоянии модели биореактора на наличие шума в процессе измерения.

English

This paper describes a new modeling methodology destined to develop a mathematical model of a bioreactor used in the bacterial oxidation process. Based on the literature review, a comparative analysis was carried out with the existing model. To customize the parameters in the bioreactor, the coefficients of the fuzzy PID controller were adjusted based on specified settings. The effectiveness of the suggested method is proven by comparing other available methods designed for tuning controllers that described in the literature. The research findings show that the proposed method is highly effective with rational regulation of bioreactor parameters. Moreover, the given method was tested in the nonlinear state of the bioreactor’ model for presence of noise within the process of measurement.

№ Имя автора Должность Наименование организации
1 Yusupbekov N.R. O‘zbekiston Respublikasi Fanlar Akademiyasi akademigi, professor Toshkent davlat texnika universiteti “Ishlab chiqarish jarayonlarini avtomatlashtirish va boshqarish” kafedrasi
2 Jumayev O.A. texnika fanlari doktori (DSc), professor, kafedra mudiri Navoiy davlat konchilik va texnologiyalar universiteti “Metrologiya, standartlashtirish va sertifikatlashtirish” kafedrasi
3 Mahmudov G.B. texnika fanlari bo‘yicha falsafa doktori (PhD), dotsent Navoiy davlat konchilik va texnologiyalar universiteti “Metrologiya, standartlashtirish va sertifikatlashtirish” kafedrasi
№ Название ссылки
1 Abdujaliliovich, J. O., Bakoyevich, M. G., & Eldor, A. (2021). Fuzzy logic controller in the management of technological processes of bacterial oxidation. Web of Scientist: International Scientific Research Journal, 2 (06), 191–197.
2 Babak, R., & Lokender, P. R. (2015, December). Concept and Application of PID Control and Implementation of Continuous PID Controller in Siemens PLCs. Indian Journal of Science and Technology, 8 (35), 1–9. doi: 10.17485/ijst/2015/v8i35/82262
3 Baqoyevich, M. G. (2023). Modeling and adjustment of a fuzzy controller in a bioreactor control system. Chemical Technology, Control and Management, 2, 14–21.
4 Chang, W. D., & Shih, S. P. (2010). PID controller design of nonlinear systems using an improved particle swarm optimization approach. Communications in Nonlinear Science and Numerical Simulation, 15 (11), 3632– 3639.
5 Igamberdiev, Kh. Z., & Mamirov, U. F. (2021). Regulyarnyy sintez sistem adaptivnogo upravleniya neopredelennymi dinamicheskimi ob”yektami [Regular synthesis of adaptive control systems for uncertain dynamic objects]. (In Russian, 215 p.). Tashkent: Bilim va intellektual salohiyat Publ.
6 Jumayev, O. A., Kovaleva, I. L., & Makhmudov, G. B. (2023). Upravleniye temperaturnym rezhimom protsessa bakterial’nogo okisleniya na osnove nechetkoy logiki [Control of the temperature regime of the bacterial oxidation process based on fuzzy logic]. (In Russian). System Analysis and Applied Informaticsa, 2, 42– 47.
7 Jumayev, O. A., Makhmudov, G. B., & Majidova, R. B. (2022). Primeneniya nechetkogo kontrollera dlya upravleniya protsessa vyshchelachivaniya zolota iz produktov bakterial’nogo vskrytiya [Application of a fuzzy controller to control the process of gold leaching from bacterial dissection products]. (In Russian). Journal of Advances in Engineering Technology, 1, 5–9.
8 Kumar, S. M. G., Jain, R., Anantharaman, N., Dharmalingam, V., & Begam K. M. M. Sh. (2008). Genetic algorithm based PID controller tuning for a model bioreactor. Indian Institute of Chemical Engineers, 50 (3), 214– 226.
9 Kumar, S. V. S., Kumar, V. R., & Reddy, G. P. (2005). Nonlinear control of bioreactors with input multiplicitiesan experimental work. Bioprocess and Biosystems Engineering, 28 (1), 45–53.
10 Kumari, K., & Mohan, B. M. (2022). Minimum t-norm leads to unrealizable fuzzy PID controllers. Information Sciences, 587, 323–334.
11 Makhmudov, G. B., Saidova, A. Kh., & Mokhilova, N. T. (2022). Modelirovaniye nechetkoy logiki dlya upravleniya protsessom bakterial’nogo okisleniya kontsentratov v reaktorakh s meshalkoy [Fuzzy logic modeling for controlling the process of bacterial oxidation of concentrates in reactors with a stirrer]. (In Russian). Modern Innovations, Systems and Technologies, 2, 0201–0214.
12 Makhmudov, G. B., Saidova, A. Kh., Mokhilova, N. T., & Ibragimova, Ch. K. (2022, April). Issledovaniye intellektual’nykh sistem upravleniya na osnove nechetkoy logiki [Research into intelligent control systems based on fuzzy logic]. (In Russian). E Conference Zone, 302–308.
13 Mu, S., Goto, S., Shibata, S., & Yamamoto, T. (2019). Intelligent position control for pneumatic servo system based on predictive fuzzy control. Computers and Electrical Engineering, 75, 112–122.
14 Nagy, Z. K. (2007). Model based control of a yeast fermentation bioreactor using optimally designed artificial neural networks. Chemical Engineering Journal, 127 (1-3), 95–109.
15 Oladele, D. A., Farouq, E., Shaibu (2019, September). An Improved Performance of Fuzzy Logic Based Controller Design for Bioreactor Process Plant. EJERS, European Journal of Engineering Research and Science, 4 (9), 177–179.
16 Prabhu, K., Dharani, P., Vijayachitra, S., & Kavya, C. (2021). Design of fuzzy – Pid controller for continuous stirred tank reactor plant. Nat. Volatiles & Essent. Oils, 8 (5), 199–205.
17 Sivakumaran, N., Radhakrishnan, T. K., & Babu, J. S. C. (2006). Identification and control of bioreactor using recurrent networks. Instrumentation Science and Technology, 34 (6), 635–651.
18 Sugeno, M. (2019). Application of Choquet Calculus to Statistics with Distorted Probabilities. IEEE Transactions on Fuzzy Systems, 27 (9), 3–15.
19 Yusupbekov, N. R., Jumayev, O. A., Mahmudov, G‘. B., & Ismoilov, M. T. (2020). Noaniq mantiq asosida intellektual boshqarish tizimlarini ishlab chiqish [Development of intelligent control systems based on fuzzy logic]. (In Uzbek). Journal of Advances in Engineering Technology, 2, 20–25.
20 Yusupbekov, N., Igamberdiev, H., & Mamirov, U. (2022). Algorithms for robust stabilization of a linear uncertain dynamic object based on an iterative algorithm. Intelligent and Fuzzy Techniques for Emerging Conditions and Digital Transformation: Proceedings of the INFUS 2021 Conference (vol. 1, pp. 225–232). Springer International Publishing.
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