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Preparing of raw materials and mineral processing
ArticleName Model for optimal control of a magnetic separator based on the Bellman dynamic programming method
ArticleAuthor N. V. Osipova

National University of Science and Technology “MISiS”, Novotroitsk affiliate (Novotroitsk, Russia):

N. V. Osipova, Cand. Eng., Associate Prof., Dept. of Automation, Institute of Information Technologies and Automated Control Systems, E-mail:


This work is devoted to the issue of research in the field of automation and control of a magnetic separator at iron ore processing plants. The substantiation of the choice of control actions is given: water flow into the separator bath and the rotational speed of its drum, ensuring the maintenance of the magnetite iron content in the concentrate at the optimum level and contributing to the reduction of its losses in tailings. The object of the research is the PBM-PP-120/300 drum semi-countercurrent magnetic separator for separating particles with a particle size of less than 1 mm at the final stages of beneficiation. Its extreme operating parameters are considered. A mathematical description of control object`s elements such as an adjustable valve, motor, magnetic separator in the form of diff erential equations is given. The main disturbances that cause the deviation of beneficiation indices out of optimal values are identified. This is the consumption of the pulp`s solid phase in the feeding of the separator and the percentage of solid in the pulp. The disadvantages of the classical PID controller are shown in comparison with the optimal controller. A brief description of the principle for constructing an optimal controller by the method of Bellman dynamic programming is given. An example is given of the operation of the mathematical model for the magnetic separator`s automatic-control system which is used in the training virtual laboratory bench at the chair for Automation of the ITACS Institute of NITU MISiS in the training of masters in the 04.04.04 direction “Management in technical systems” as a part of the teaching of the subject “Mathematical modeling of objects and control systems”. The results of modeling in the mode of manual and automatic control of the separator are presented. Thanks to the obtained time diagrams, it was possible to show that the presence of the optimal regulator makes it possible to stabilize the content of magnetite iron in the concentrate within the specified deviation limits, and its tail loss is not higher than the permissible value. This reduces the service time of the magnetic separator spent on the search for operating modes in the conditions of fluctuations in the properties of the initial pulp stream.

keywords Magnetic separation, concentrate, tails, optimal control, Bellman dynamic programming, Siemens Simatic S7-300, STEP 7, SCADA system, Riccati equation, quality functional

1. Ganzhenko I. М., Yakubaylik E. К., Zarshikova G. G., Kamalova Т. B., Alekseeva L. А. Reduction of the contamination of the final concentrate at the Abagur dressing plant. Chernaya metallurgiya. Byulleten nauchno-tekhnicheskoy i ekonomicheskoy informatsii. 2017. No. 3(1407). pp. 39–44.
2. Nesterenko I. А., Nesterenko А. P. Correction function for calculating the magnetic field intensity gradient of the drum separator. Vestnik Luganskogo natsionalnogo universiteta imeni Vladimira Dalya. 2018. No. 11(17). pp. 173–179.
3. Osipova N. V. Synthesis of an asymptotic observer for a control system for a magnetic separator in iron ore beneficiation. Gorny informatsionno-analiticheskiy buylleten. 2018. No. 6. pp. 153–160.
4. Osipova N. V. The use of the Kalman filter for automatic control of indicators of iron ores magnetic concentration. Izvestiya vysshikh uchebnykh zavedeniy. Chernaya metallurgiya. 2018. 61(5). pp. 372–377.
5. Pevzner L. D. Control system theory. Saint-Petersburg: Izdatelstvo Lan. 2018. 420 p.
6. Pelevin А. Е., Sytykh N. А. Iron concentrate stage separation by means of drum magnetic separator with modified separating bath. Obogashchenie Rud. 2016. No. 4(364). pp. 10–15.
7. Yu J., Han Y., Li Y., Gao P. Recovery and separation of iron from iron ore using innovative fluidized magnetization roasting and magnetic separation. Journal of Mining and Metallurgy. 2017, Iss. 54(1). pp. 1–12.
8. Morkun V. S., Morkun N. V., Tron V. V., Dotsenko I. A. Adaptive control system for the magnetic separation process. Sustainable Development of Mining Territories. 2018. Vol. 10, Iss. 4(38). pp. 545–557.
9. Osipova N. V. Model of stabilization of the quality of iron-ore concentrate in the process of magnetic separation with the use of extreme regulation. Metallurgist. 2018. Vol. 62. No. 3-4. pp. 303–309.
10. Shaikh Y., Seibert C., Kampeis P. Study on Optimizing High-Gradient Magnetic Separation, Part 1: Improvement of Magnetic Particle Retention Based on CFD Simulations. World Journal of Condensed Matter Physics. 2016. No. 6. pp. 123–136.
11. Wenguang Du, Song Yang, Feng Pan, Ju Shangguan, Jie Lu, Shoujun Liu, Huiling Fan. Hydrogen Reduction of Hematite Ore Fines to Magnetite Ore Fines at Low Temperatures. Journal of Chemistry. 2017. Vol. 2017. pp. 1–11.
12. Xianlin Zhou, Deqing Zhu, Jian Pan, Yanhong Luo and Xinqi Liu. Upgrading of High-Aluminum Hematite-Limonite Ore by High Temperature Reduction-Wet Magnetic Separation Process. Metals. 2016. Vol. 57. No. 6. pp. 21–27.

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