Сhigitli paxtani quritish jarayonining harorat-namlik rejimini fuzzy-PID rostlagich asosida boshqarish
##semicolon##
paxta xomashyosi##common.commaListSeparator## quritish##common.commaListSeparator## namlik##common.commaListSeparator## fuzzy-mantiq##common.commaListSeparator## PID-rostlagich##common.commaListSeparator## adaptiv boshqarish##common.commaListSeparator## harorat##common.commaListSeparator## avtomatik boshqarishAbstrak
Maqolada сhigitli paxta xomashyosini quritish jarayonining harorat-namlik rejimini boshqarish uchun fuzzy-PID rostlagichga asoslangan adaptiv boshqarish tizimini shakllantirish masalalari ko‘rib chiqilgan. Quritish obyekti boshlang‘ich namlik, quritish agentining harorati va sarfi, xomashyo sarfi, tashqi muhit parametrlari hamda texnologik kechikishlar ta’sir qiladigan ko‘p omilli, nochiziqli va inersion obyekt sifatida qaralgan. Klassik PID-rostlagichning o‘zgarmas sozlamalari obyekt parametrlari o‘zgarganda boshqarish sifatini pasaytirishi mumkinligi asoslangan. Rostlash xatoligi e va uning o‘zgarishi Δe asosida Kp, Ki va Kd koeffitsientlarini real vaqt rejimida tuzatadigan noaniq mantiqiy supervizor taklif etilgan. Kirish va chiqish lingvistik o‘zgaruvchilari, tegishlilik funksiyalari, 49 ta qoidali baza va Mamdani xulosalash algoritmini shakllantirish tamoyillari berilgan. Taklif etilgan struktura paxta namligi va texnologik yuklama o‘zgarganda rostlagich parametrlarini moslashtirish, chiqish namligini berilgan qiymat atrofida barqarorlashtirish va an’anaviy PID tizimiga nisbatan boshqarishning moslashuvchanligini oshirish uchun nazariy asos yaratadi
##submission.citations##
Byler R.K., Anthony W.S. Initial Experiences in Computer Control of Cotton Gin Drying // Applied Engineering in Agriculture. 1992. Vol. 8, No. 5. P. 703–709. DOI: 10.13031/2013.26142.
Baker K.D. Temperature Control for Seed Cotton Drying Systems // Applied Engineering in Agriculture. 2012. Vol. 28, No. 6. P. 885–890.
Yunusnova S.T., Holmatov D.A., Atajonov M.O., Huzanazarov U. Formalization of the Cotton Drying Process Based on Heat and Mass Transfer Equations // IIUM Engineering Journal. 2020. Vol. 21, No. 2. P. 256–265. DOI: 10.31436/iiumej.v21i2.1456.
Zadeh L.A. The Concept of a Linguistic Variable and its Application to Approximate Reasoning // Information Sciences. 1975. Vol. 8. P. 199–249.
Mamdani E.H. Application of Fuzzy Algorithms for Control of Simple Dynamic Plant // Proceedings of the Institution of Electrical Engineers. 1974. Vol. 121, No. 12. P. 1585–1588.
Hosseinpour S., Martynenko A. Application of Fuzzy Logic in Drying: A Review // Drying Technology. 2022. Vol. 40, No. 5. P. 797–826. DOI: 10.1080/07373937.2020.1846192.
Feng X., Guo C., Li P., Yang B., Li H., Gao H., Zhang C. A Study on Drying Control of Seed Cotton Based on BP Neural Network Model // IOP Conference Series: Earth and Environmental Science. 2021. Vol. 697. 012007. DOI: 10.1088/1755-1315/697/1/012007.
Yunusova S.T. Simulation of a Trained Neural Network of a Fuzzy Logic Regulation System Based on the Cotton Drying Process // Technical Science and Innovation. 2020. ROI: 11.0008/A0120-0030.
Siddikov I.X., Yunusova S.T., Xujanazarov U.O. Nechetko-logicheskoye regulirovaniye protsessa sushki xlopka // Muhammad Al-Xorazmiy avlodlari. 2020. No. 2(12). P. 43–47.
Hosseinpour S., Martynenko A. An Adaptive Fuzzy Logic Controller for Intelligent Drying // Drying Technology. 2023. Vol. 41, No. 7. P. 1110–1132. DOI: 10.1080/07373937.2022.2119996.
Усков А.А., Кузьмин А.В. Интеллектуальные технологии управления. Искусственные нейронные сети и нечеткая логика. – М.: Горячая Линия – Телеком, 2004. – 143 с.
Yusupbekov N.R., Aliyev R.A., Aliyev R.R., Yusupbekov A.N. Boshqarishning intellektual tizimlari va qaror qabul qilish. Toshkent: O‘zbekiston milliy ensiklopediyasi, 2015. 490 b.
