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AUTOMATIC CONTROL SYSTEMS
Название Intelligent control method for the bacterial leaching process of gold-bearing sulfide ores
DOI 10.17580/or.2025.01.08
Автор Zhumaev O. A., Makhmudov G. B., Ismoilov M. T., Pulatov V. B.
Информация об авторе

Navoi State University of Mining and Technologies (Navoi, Uzbekistan)
Jumaev O. A., Professor, Doctor of Engineering Sciences, Professor, jumaev5216@mail.ru
Makhmudov G. B., Associate Professor, PhD in Engineering Sciences, Associate Professor, mahmudov.giyos@mail.ru
Ismoilov M. T., Associate Professor, PhD in Engineering Sciences, Associate Professor, imuxriddint@mail.ru

 

Navoi Mining and Metallurgical Plant (Navoi, Uzbekistan)
Pulatov V. B., Head of the Production Automation Department, v.pulatov@ngmk.uz

Реферат

This paper discusses the development of an intelligent control system (ICS) designed to optimize the biotechnological processing of gold-bearing sulfide concentrates. The focus is on the fuzzy control of key process parameters such as temperature, slurry pH, and the air flow rate supplied under pressure to the bioreactor module. These parameters are critical for maintaining the appropriate concentration of ferrous iron ions in the slurry, which directly influences the efficiency of the bacterial oxidation (BO) process. The system operates based on real-time sensor data, allowing it to promptly respond to variations and maintain optimal bioreactor conditions. The proposed control system is a sophisticated hierarchical hardware and software structure, incorporating software modules designed for fuzzy control. A rule base for the fuzzy controllers was developed, and a simulation model of the control system was created using the Fuzzy Logic Toolbox in MATLAB. This model not only predicts the system’s behavior under various conditions but also optimizes control parameters to maximize BO efficiency. By employing fuzzy logic for process parameter monitoring and control, the system enhances adaptability to input parameter variations and reduces the impact of external disturbances. Simulation results for temperature control in the bioreactor show a 2.1 % improvement in accuracy with the fuzzy logic con trolsystem, compared to the traditional PID controller. Additionally, the system results in reduced consumption of reagents, such as sulfuric acid and cyanide.

Ключевые слова Sulphide concentrates, bacterial oxidation, fuzzy controller, intelligent control system, microprocessor system, membership functions, rule base
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