Adaptive algorithms for managing mineral raw materials benefication processes for sustainable development of mining territories
Адаптивные алгоритмы управления процессами обогащения минерального сырья для устойчивого развития горнопромышленных территорий
Botirov T.V. Kadirov Y.B. Kovalev I.V. Ormanbekova A.A.
2025North Caucasian Institute of Mining and Metallurgy, State Technological University
Sustainable Development of Mountain Territories
2025#17Issue 31748 - 1759 pp.
Introduction. Sustainable development of mining territories requires energy-efficient and environmentally oriented mineral beneficiation technologies. The stochastic and nonstationary nature of flotation processes necessitates the implementation of adaptive control systems. Purpose of the research. To develop and substantiate adaptive control algorithms for mineral beneficiation processes aimed at improving operational stability, energy efficiency, and environmental safety of mining enterprises. Materials and methods. Stochastic identification techniques based on input–output relationships and autoregressive moving-average models were applied. Parameter estimation was performed using the conditional maximum likelihood method with iterative procedures, including Newton’s method combined with Tikhonov regularization. Dynamic models of flotation processes with time delays and random disturbances were considered. Results. Algorithms for robust estimation of system parameters and states were developed, enabling the synthesis of adaptive control systems under model uncertainty. A functional scheme of an adaptive flotation control system was proposed to stabilize concentrate ash content in the presence of significant delays and stochastic disturbances. Discussion. The implementation of adaptive algorithms reduces variance of concentrate quality indicators, optimizes reagent consumption, and increases product yield. Regularization of iterative procedures ensures computational stability and reduces sensitivity to data inaccuracies. Conclusion. The proposed algorithms provide a scientific and practical basis for intelligent control of mineral beneficiation processes. Resume. Adaptive identification and control methods enhance flotation efficiency, reduce energy and material consumption, and improve environmental performance of mining enterprises. Suggestions for practical applications and directions for future research. Industrial implementation at beneficiation plants is recommended. Future research should focus on integration with digital mining platforms and extension of adaptive control methods to other mineral processing operations.
adaptive control , environmental efficiency , flotation , mineral processing , mining , Newtons method , stochastic identification
Text of the article Перейти на текст статьи
Department of Automation and Control, Navoi State Mining and Technological University, Navoi, 210100, Uzbekistan
Department of Software Engineering, Siberian Federal University, 79, Svobodny avenue, Krasnoyarsk, 660041, Russian Federation
Department of Information Technologies and Mathematical Support of Information Systems, Krasnoyarsk State Agrarian University, 90, Mira Ave., Krasnoyarsk, 660049, Russian Federation
Department of Automation and Robotics, Almaty Technological University, 100, Tobe bi str., Almaty, 050012, Kazakhstan
Department of Automation and Control
Department of Software Engineering
Department of Information Technologies and Mathematical Support of Information Systems
Department of Automation and Robotics
10 лет помогаем публиковать статьи Международный издатель
Книга Публикация научной статьи Волощук 2026 Book Publication of a scientific article 2026