Development of the multicoupling dynamic model of process of extraction of phosphoric acid on the basis of an artificial neural network

Authors

D.P Mukhitdinov, Doctor of Technical Sciences, Professor, Department of Automation of Production Processes, Tashkent State Technical University. Tel .: +998946042380 (m.);
F.A Ergashev, Senior Lecturer, Department of Metrology, Standardization and Certification, TSTU, Tel .: (+99890) 315-05-25,Follow
A.V Schultz, Master of the Department of Automation of Production Processes, Tashkent State Technical University. Tel .: +998936051311 (m.).

Abstract

The deals with the problems of mathematical modeling and optimization of complex technological processes for obtaining extraction phosphoric acid based on the use of an artificial neural network. The use of the function of changing the concentrations from the residence time of the components in the reactor to find the mass consumption of phosphoric flour is substantiated and proposed. The work of a trained neural network for stabilizing perturbations is shown when input of input data with distortion is fed to its input.

First Page

52

Last Page

56

References

1. N.R.YUsupbekov, D.P.Muhitdinov, A.V.SHul'c, “Obzor aktual'ny'h tehnologiy proizvodstva e`kstrakcionnoy fosfornoy kisloty'” [Review of relevant technologies for the production of wet phosphoric acid], Himicheskaya tehnologiya. Kontrol' i upravlenie, no. 3, pp. 5, 2017.

2. S.V. Dorojkin, B.M. Dolgonosov, Racional'naya organizaciya stadii rastvoreniya ftorapatita v proizvodstve e`kstrakcionnoy fosfornoy kisloty' [Rational organization of the dissolution stage of fluorapatite in the production of wet phosphoric acid], Himicheskaya promy'shlennost', no. 9, pp. 521-525, 1992 (in Russian).

Recommended Citation

Mukhitdinov, D.P; Ergashev, F.A; and Schultz, A.V (2018) "Development of the multicoupling dynamic model of process of extraction of phosphoric acid on the basis of an artificial neural network," Chemical Technology, Control and Management: Vol. 2018: Iss. 2, Article 10.
DOI: https://doi.org/10.34920/2018.3.52-56