Determination of a kiln model during normal operation

One of the main requirements for the efficiency of automatic control systems at enrichment plants is the adequacy of the mathematical model of the controlled object used in the design and adjustment of the control system. However, even with an adequate mathematical model of the control object, over time, the operation of the automatic control system may become ineffective due to changes in the parameters of the control object used in the development of the system. Thus, there is a need for periodic updating of the parameters of the controlled object. Such parameter adjustment is especially important for objects with the return of part of the initial substance from the output of the object to its input – objects with recirculation (recycle). For enrichment processes, such objects in some cases are crushers, screens, mills and a number of other process units. In addition, objects with recycle are often characterized by large transport delays in the flows of ore and pulp. When creating automatic control systems in this case, an accurate mathematical model of the controlled object is needed. In particular, such a model is absolutely necessary for using the Smith regulator recommended for working with objects with recycling. Due to the aging of mechanisms, changes in the physical properties of ore and pulp, and other conditions, the parameters of control objects change and require periodic adjustment, which has been repeatedly indicated in various studies. The paper proposes to use the apparatus of the theory of random functions to update the mathematical description of enrichment objects with recycle, based on the Wiener-Hopf equation, without conducting special experiments in normal operation mode.

Keywords: autocorrelation function, intercorrelation function, technological process, automatic control system, model adjustment, Wiener-Hopf equation, transfer function, control object.
For citation:

Leonov R. E., Patrakov S. S. Determination of a kiln model during normal operation. MIAB. Mining Inf. Anal. Bull. 2025;(1-1):155-164. [In Russ]. DOI: 10.25018/0236_ 1493_2025_11_0_155.

Acknowledgements:
Issue number: 1
Year: 2025
Page number: 155-164
ISBN: 0236-1493
UDK: 622.7:681.5
DOI: 10.25018/0236_1493_2025_11_0_155
Article receipt date: 16.07.2024
Date of review receipt: 06.12.2024
Date of the editorial board′s decision on the article′s publishing: 10.12.2024
About authors:

R.E. Leonov1, Cand. Sci. (Eng.), Assistant Professor, Professor, e-mail: lprep2011@mail.ru, ORCID ID: 0000-0002-2531-8336,
S.S. Patrakov1, Graduate Student, e-mail: patrakov.sema@mail.ru, ORCID ID: 0009-0007-9173-6935,
1 Ural State Mining University, 620144, Ekaterinburg, Russia.

 

For contacts:

R.E. Leonov, e-mail: lprep2011@mail.ru.

Bibliography:

1. Mukonin A. K., Medvedev V. A., Trubetskoy V. A., Tonyan D. A., Goremykin S. A., Sitnikov N. V. Improving the reliability of automatic process control systems. Bulletin of Vitebsk State Technological University. 2020, no. 4, pp. 56—63. [In Russ]. DOI: 10.25987/VSTU.2020.16.4.007.

2. Loginov E. L., Loginov A. E. Improving the quality and reliability of management of complex systems of critical energy infrastructure in the UES of Russia. National Interests: Priorities and Security. 2012, no. 38, pp. 31—37. [In Russ].

3. Nagiev M. F. Uchenie o retsirkulyatsionnykh protsessakh v khimicheskoy tekhnologii [The doctrine of recycling processes in chemical technology], Moscow, Izd-vo AN SSSR, 1958, 243 p.

4. Tsypin E. F. Preliminary concentration. Minerals and Mining Engineering. 2001, no. 4-5, pp. 82—104. [In Russ].

5. Kozin V. Z., Komlev A. S., Volkov P. S. Concentration operations efficiency in the schemes of samples preparation. Gornyi Zhurnal. 2017, no. 3, pp. 83—87. [In Russ].

6. Prokofiev E. Z., Efremov V. N., Lapin E. S. Development of algorithmic structures of models of technological complexes of processes of preparation and enrichment of minerals. News of the Ural State Mining University. 2000, no. 9, pp. 47—56. [In Russ].

7. Marasanov V. M., Dyldin G. P. Mathematical description of the crushing process in a jaw crusher. Minerals and Mining Engineering. 2017, no. 8, pp. 82—91. [In Russ]. DOI: 10.21440/0536-10282017-8-82-91.

8. Uteush Z. V., Uteush E. V. Upravlenie izmel'chitel'nymi agregatami [Control of grinding units], Moscow, Mashinostroenie, 1973, 280 p.

9. Leontiev A. A., Tauger V. M., Volkov E. B. The dynamics of a laden skip of the shaft pneumatic winding plant during acceleration. Minerals and Mining Engineering. 2021, no. 1, pp. 115—121. [In Russ]. DOI: 10.21440/0536-1028-2021-1-115-121.

10. Morozovskiy V. T. Mnogosvyaznye sistemy avtomaticheskogo regulirovaniya [Multiconnected automatic control systems], Moscow, Energiya, 1970.

11. Stanisławski R. Modified Mikhailov stability criterion for continuous-time noncommensurate fractional-ordersystems. Journal of the Franklin Institute. 2022, vol. 359, no. 4, pp. 271—283. [In Russ]. DOI: 10.1016/j.jfranklin.2022.01.022.

12. Kundrata J., Fujimoto D., Hayashi Yu., Baric A. Comparison of Pearson correlation coefficient and distance correlation in correlation power analysis on digital multiplier. 43rd International Convention on Information, Communication and Electronic Technology (MIPRO), 2020. DOI: 10.23919/ MIPRO48935.2020.9245325.

13. Rusakova Yu. O., Plavnik A. G., Vashurina M. V., Khramtsova A. L. Analysis of the main factors determining the value of the specific flow rate of a water intake well. News of the Ural State Mining University. 2023, no. 1 (69), pp. 78—87. [In Russ]. DOI: 10.21440/2307-2091-2023-1-78-87.

14. Solodovnikov V. V., Uskov A. S. Statisticheskiy analiz ob"ektov regulirovaniya. Statisticheskie metody opredeleniya dinamicheskikh kharakteristik ob"ektov avtomaticheskogo regulirovaniya v protsesse ikh normal'noy ekspluatatsii [Statistical analysis of regulatory objects. Statistical methods for determining the dynamic characteristics of automatic control facilities during their normal operation], Moscow, Mashgiz, 1960, 131 p.

15. Smagin V. A. Solution of the Wiener-Hopf integral equation by the hyperdelt approximation method. Intellectual Technologies on Transport. 2016, no. 1, pp. 39—45.

16. Maurya G., Sharma B. L. Scattering by two staggered semi-infinite cracks on square lattice: an application of asymptotic Wiener—Hopf factorization. Zeitschrift für angewandte Mathematik und Physik. 2019, vol. 70, article 133. DOI: 10.1007/s00033-019-1183-2.

17. Anisimov S. A., Zaytseva I. S., Raybman N. S., Yaralov A. A. Tipovye lineynye modeli ob"ektov upravleniya [Typical linear models of control objects], Moscow, Energoatomizdat, 1983, 264 p.

18. Deych A. M. Metody identifikatsii dinamicheskikh ob"ektov [Methods of identification of dynamic objects], Moscow, Energiya, 1979, 240 p.

19. Baskys A. Switched-delay smith predictor for the control of plants with response-delay asymmetry. Sensors. 2023, vol. 23, article 258. DOI: 10.3390/s23010258.

20. Luo Y., Xue W., He W., Nie K., Mao Y., Guerrero J. M. Delay-compound-compensation control for photoelectric tracking system based on improved smith predictor scheme. IEEE Photonics Journal. 2022, vol. 14, no. 3. DOI: 10.1109/JPHOT.2022.3164202.

21. Potemkin V. G. MATLAB 6: Sreda proektirovaniya inzhenernykh prilozheniy [MATLAB 6: Environment for designing engineering applications], Moscow, Dialog MIFI, 2003, 448 p.

Подписка на рассылку

Подпишитесь на рассылку, чтобы получать важную информацию для авторов и рецензентов.