AUTOMATIC REGULATION SYSTEM FOR SULFUR PURIFICATION OF NATURAL GAS
Keywords:
fuzzy system, control object, parameter optimization, method of minimum integral quality criterion, regularization
Abstract
Algorithms for the synthesis of a fuzzy system for automatic control of natural gas desulfurization processes are presented. When forming the problem of analytical design of the regulator to control the temperature of the upper part of the column, the method of the minimum of the integral quality criterion was used. The presented results of mathematical and computer modeling showed that the designed optimal combined system can provide the required quality of the column temperature control process. The model parameters were estimated using the recursive filtering identification algorithm modified for the multidimensional case. In this case, the synthesis of a control algorithm consists of determining a control strategy that minimizes the variance of the controlled coordinate. The results of numerical analysis have confirmed their effectiveness, which makes it possible to use them in solving applied problems of optimizing the parameters of a combined fuzzy control system for the process of desulfurization of natural gas.
References
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[2] Iskusstvenniy intellekt i intellektualniye sistemi upravleniya / I. M. Makarov i dr., -M.: Nauka, 2006. - 333 s.
[3] Vasilyev V.I., Ilyasov B.G. Intellektualniye sistemi upravleniya. Teoriya i praktika. Uchebnoye posobiye. - M.: Radiotexnika, 2009. - 392 s.
[4] Pupkov K.A., Konkov V.G. Intellektualniye sistemi. – M.: MGTU im.Baumana, 2003. – 348 s.
[5] Igamberdiyev X.Z., Sevinov J.U., Zaripov O.O. Regular methods and algorithms for the synthesis of adaptive control systems with customizable models.- Tashkent, TashGTU, 2014. 160 p.
[6] Golubyatnikov V.A., Shuvalov V.V. Avtomatizatsiya proizvodstvennix protsessov v ximicheskoy promishlennosti: Uchebn. dlya texnikumov. – 2 ye izd., pererab. i dop. –M.: Ximiya, 1985. – 352 s.
[7] Texnologicheskiye osnovi i modelirovaniye protsessov promislovoy podgotovki nefti i gaza: Uchebnoye posobiye /Kravsov A.V. [i dr.]. Tomsk: izd-vo Tomskogo politexn. un-ta, 2012. – 128 s.
[8] Zabolotnov Y.M. Optimalnoye upravleniye neprerivnimi dinamicheskimi sistemami. Uchebnoye posobiye. Samara: Samarskiy gosudarstvenniy aerokosmicheskiy universitet imeni akademika S. P. Koroleva, 2005, 129 s.
[9] Kafarov V.V., Meshalkin V.P., Perov V.L. Matematicheskiye osnovi avtomatizirovannogo proyektirovaniya ximicheskix proizvodstv. – M.: Ximiya, 1979.
[10] Molokanov Y.K. Protsessi i apparati neftegazopererabotki. – M.: Ximiya,1999.
[11] Lanchakov G.A., Kulkov A.N., Zibert G.K. Texnologicheskiye protsessi podgotovki prirodnogo gaza i metodi rascheta oborudovaniya. M.: Nedra-Biznessentr, 2000, 279s.
[12] N.R.Yusupbekov, H.Z. Igamberdiev, J.U.Sevinov. Formalization of Identification Procedures of Control Objects as a Process in the Closed Dynamic System and Synthesis of Adaptive Regulators. Journal of Advanced Research in Dynamical and Control Systems. Volume 12, 06-Special Issue. Pages: 77-88. DOI:10.5373/JARDCS/V12SP6/SP20201009.
[13] Yusupbekov A.N., Sevinov J.U., Mamirov U.F., Botirov T.V.Synthesis Algorithms for Neural Network Regulator of Dynamic System Control.Yusupbekov A.N., Sevinov J.U., Mamirov U.F., Botirov T.V. Synthesis Algorithms for Neural Network Regulator of Dynamic System Control. (2021) Synthesis Algorithms for Neural Network Regulator of Dynamic System Control. In: Aliev R.A., Kacprzyk J., Pedrycz W., Jamshidi M., Babanli M., Sadikoglu F.M. (eds) 14th International Conference on Theory and Application of Fuzzy Systems and Soft Computing – ICAFS-2020. ICAFS 2020. Advances in Intelligent Systems and Computing, vol 1306. Springer, Cham. https://doi.org/10.1007/978-3-030-64058-3_90
[14] Sevinov J.U., Mallaev А.R., Xusanov S.N.Algorithms for the Synthesis of Optimal Linear-Quadratic Stationary Controllers. Sevinov J.U., Mallaev A.R., Xusanov S.N. (2021) Algorithms for the Synthesis of Optimal Linear-Quadratic Stationary Controllers. In: Aliev R.A., Yusupbekov N.R., Kacprzyk J., Pedrycz W., Sadikoglu F.M. (eds) 11th World Conference “Intelligent System for Industrial Automation” (WCIS-2020). WCIS 2020. Advances in Intelligent Systems and Computing, vol 1323. Springer, Cham. https://doi.org/10.1007/978-3-030-68004-6_9
[15] Leonenkov A.V. Nechetkoye modelirovaniye v srede MATLAB i Fuzzy TECH. –SPb.: BXV Peterburg, 2005.
[16] Yegupov N.D. Metodi robastnogo, neyro-nechyotkogo i adaptivnogo upravleniya: Uchebnik / Pod red. N.D. Yegupova, 2-ye izd. - M.: Izd-vo MGTU im. Baumana, 2002.- 744 s.
[17] Yusupbekov N.R., Nurmuhamedov H.S., Zokirov S.G. Kimyoviy texnologiya asosiy jarayon va qurilmalari. –T.: «Fan va texnologiya», 2015, - 848 b.
[18] Lanchakov G.A., Kulkov A.N., Zibert G.K. Texnologicheskiye protsessi podgotovki prirodnogo gaza i metodi rascheta oborudovaniya. -M.: Nedra-Biznessentr, 2000. – 279 s.
Published
2021-06-15
How to Cite
Sevinov J. U, & Ashuraliyev A. A. (2021). AUTOMATIC REGULATION SYSTEM FOR SULFUR PURIFICATION OF NATURAL GAS. International Journal on Orange Technologies, 3(6), 25-29. https://doi.org/10.31149/ijot.v3i6.1948
Section
Articles
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