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<p>This paper presents a&#xa0;parametric analysis methodology for supervisory control of the electrolytic copper refining process. The approach employs an antisymmetric dynamic regulator to compensate for deviations in key process parameters, including electrolyte composition, current density, and circulation rate. The developed mathematical model captures the input–output relationships of the system, enabling precise prediction and adjustment of operating conditions. Modeling was conducted to assess the influence of sulfuric acid concentration, copper content, and electrolyte circulation rate on productivity and current efficiency. The results demonstrate that the proposed method effectively mitigates disturbances, stabilizes current efficiency, and maintains productivity within target ranges. Additionally, the identification of optimal operating ranges contributes to improved energy efficiency and reduced material consumption. The model’s integration into a&#xa0;SCADA-based control system enables real-time monitoring and high responsiveness, enhancing both operational reliability and adaptability.</p>

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Parametric analysis for supervisory control of cathode copper production

  • 期刊论文

  • 发表日期：

    2025年8月7日

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  • Olga K. Mansurova,
  • Huy H. Nguen

摘要

This paper presents a parametric analysis methodology for supervisory control of the electrolytic copper refining process. The approach employs an antisymmetric dynamic regulator to compensate for deviations in key process parameters, including electrolyte composition, current density, and circulation rate. The developed mathematical model captures the input–output relationships of the system, enabling precise prediction and adjustment of operating conditions. Modeling was conducted to assess the influence of sulfuric acid concentration, copper content, and electrolyte circulation rate on productivity and current efficiency. The results demonstrate that the proposed method effectively mitigates disturbances, stabilizes current efficiency, and maintains productivity within target ranges. Additionally, the identification of optimal operating ranges contributes to improved energy efficiency and reduced material consumption. The model’s integration into a SCADA-based control system enables real-time monitoring and high responsiveness, enhancing both operational reliability and adaptability.