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Synthesis of an Electric Arc Furnace Electrode Movement Control System Based on Feedback Linearization with PI or PI μ Controllers

Author

Listed:
  • Andriy Lozynskyy

    (Faculty of Transport, Electrical Engineering and Computer Science, Casimir Pulaski Radom University, 26-600 Radom, Poland
    Institute of Power Engineering and Control System, L’viv Polytechnic National University, 79-013 L’viv, Ukraine)

  • Jacek Kozyra

    (Faculty of Transport, Electrical Engineering and Computer Science, Casimir Pulaski Radom University, 26-600 Radom, Poland)

  • Andriy Kutsyk

    (Institute of Power Engineering and Control System, L’viv Polytechnic National University, 79-013 L’viv, Ukraine
    Faculty of Electrical and Computer Engineering, Rzeszow University of Technology, 35-959 Rzeszow, Poland)

  • Zbigniew Łukasik

    (Faculty of Transport, Electrical Engineering and Computer Science, Casimir Pulaski Radom University, 26-600 Radom, Poland)

  • Aldona Kuśmińska-Fijałkowska

    (Faculty of Transport, Electrical Engineering and Computer Science, Casimir Pulaski Radom University, 26-600 Radom, Poland)

  • Lidiia Kasha

    (Institute of Power Engineering and Control System, L’viv Polytechnic National University, 79-013 L’viv, Ukraine)

Abstract

An approach is proposed for the synthesis of the control system for the electrode movement of an arc steelmaking furnace based on a combination of the feedback linearization method and a traditional PI controller. The application of fractional PI μ controllers in such a control system using the Caputo–Fabrizio representation for their description is analyzed. The use of such controllers provides transient characteristics ranging from those of a modal control system to the characteristics of a system with a classical PI controller that was developed using feedback linearization. The comparison between proposed controllers is conducted by the ISE and ITAE indexes. The effectiveness of the synthesized control systems is demonstrated by research results using both single-phase and three-phase models of the electrode movement system in an arc steelmaking furnace.

Suggested Citation

  • Andriy Lozynskyy & Jacek Kozyra & Andriy Kutsyk & Zbigniew Łukasik & Aldona Kuśmińska-Fijałkowska & Lidiia Kasha, 2025. "Synthesis of an Electric Arc Furnace Electrode Movement Control System Based on Feedback Linearization with PI or PI μ Controllers," Energies, MDPI, vol. 18(18), pages 1-25, September.
    • Handle: RePEc:gam:jeners:v:18:y:2025:i:18:p:4873-:d:1748832
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    References listed on IDEAS

    as
    1. Manuela Panoiu & Caius Panoiu, 2024. "Hybrid Deep Neural Network Approaches for Power Quality Analysis in Electric Arc Furnaces," Mathematics, MDPI, vol. 12(19), pages 1-30, September.
    2. Andriy Lozynskyy & Jacek Kozyra & Zbigniew Łukasik & Aldona Kuśmińska-Fijałkowska & Andriy Kutsyk & Yaroslav Paranchuk & Lidiia Kasha, 2022. "A Mathematical Model of Electrical Arc Furnaces for Analysis of Electrical Mode Parameters and Synthesis of Controlling Influences," Energies, MDPI, vol. 15(5), pages 1-19, February.
    3. Jacek Kozyra & Andriy Lozynskyy & Zbigniew Łukasik & Aldona Kuśmińska-Fijałkowska & Andriy Kutsyk & Lidiia Kasha, 2023. "Electric Arc Furnace Electrode Movement Control System Based on a Fuzzy Arc Length Identifier," Energies, MDPI, vol. 16(21), pages 1-16, October.
    4. Loredana Ghiormez & Manuela Panoiu & Caius Panoiu, 2024. "Fuzzy Logic Controller for Power Control of an Electric Arc Furnace," Mathematics, MDPI, vol. 12(21), pages 1-26, November.
    5. Raul Garcia-Segura & Javier Vázquez Castillo & Fernando Martell-Chavez & Omar Longoria-Gandara & Jaime Ortegón Aguilar, 2017. "Electric Arc Furnace Modeling with Artificial Neural Networks and Arc Length with Variable Voltage Gradient," Energies, MDPI, vol. 10(9), pages 1-11, September.
    Full references (including those not matched with items on IDEAS)

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