Electric Arc Furnace Electrode Movement Control System Based on a Fuzzy Arc Length Identifier

Kozyra, Jacek; Lozynskyy, Andriy; Łukasik, Zbigniew; Kuśmińska-Fijałkowska, Aldona; Kutsyk, Andriy; Kasha, Lidiia

doi:10.3390/en16217281

Cited by 3 publications

(1 citation statement)

References 27 publications

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“…This transformation allowed the authors to apply classical control theory approaches to the synthesis of control influences. The elimination of mutual influences between the phases of an EAF in the process of control signal synthesis in the electrode movement system, as shown in [54], is possible by using arc length control.…”

Section: Introductionmentioning

confidence: 99%

Increasing the Level of Autonomy of Control of the Electric Arc Furnace by Weakening Interphase Interactions

Kozyra,

Lozynskyy,

Łukasik

et al. 2023

Energies

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Steelmaking is one of the most energy-intensive industries, so improving control efficiency helps to reduce the energy used to produce a tonne of steel. Mutual influences between the phases of an electric arc furnace in available electrode movement control systems cause unproductive electrode movements as a reaction to the redistribution of currents among the phases of a three-phase power supply system due to changes in arc length in one of the phases. The nonlinearity of the characteristics of an electric arc furnace significantly complicates the ability to provide autonomous electrode movement control. The approach proposed in this paper, based on the formation of a matrix of mutual influences with variable coefficients, significantly improves the per-phase autonomy of the electrode movement control system. Nonlinear dependences of the mutual influence coefficients as a function of the current increment in the phase in which the disturbance occurred are obtained. Thus, it is possible to practically eliminate unproductive electrode movements in existing control systems by avoiding the traditional use of a dead zone, which reduces the control quality in the zone of small disturbances. The complex of experiments performed using the mathematical model demonstrate that the mutual influence improves the dynamic properties of the electrode movement system in certain operating modes.

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Section: Introductionmentioning

confidence: 99%

Increasing the Level of Autonomy of Control of the Electric Arc Furnace by Weakening Interphase Interactions

Kozyra,

Lozynskyy,

Łukasik

et al. 2023

Energies

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Fuzzy Logic Controller for Power Control of an Electric Arc Furnace

Ghiormez,

Panoiu,

Panoiu

2024

Mathematics

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Electric Arc Furnaces (EAFs) are widely used in the steel manufacturing industry to melt scrap steel by employing a large number of electric arcs. EAFs play an important role in ensuring the efficient production of steel. However, their nonlinear and variable load characteristics have a significant impact on power quality. Because the active power of an electric arc depends on its length, a system for controlling the electrode positions is necessary. This paper presents a control system based on a fuzzy logic controller for the active power control of an electric arc furnace. Individual simulation scenarios were chosen with both reference values and the process taken into consideration. The reference, constant value, step variation, and the sequence of step variation were investigated, as well as step disturbances and the sequence of step disturbances from the viewpoint of the process. Furthermore, the procedure of changing the tap on a transformer was investigated. The proposed solution minimizes the time required for charge elaboration, but the main benefit is that there are no additional costs in the implementation process because the installation remains identical, with the only changes being improvements to soft control management.

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System Identification for Robust Control of an Electrode Positioning System of an Industrial Electric Arc Melting Furnace

Feliu-Batlle,

Rivas-Perez,

Borges-Rivero

et al. 2024

Processes

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Through system identification for robust control methods and utilizing real-time experimental field data, a comprehensive mathematical model is derived that represents the dynamic performance of a single electrode positioning system (EPS) in an industrial electric arc melting furnace (EAF). This EPS is characterized by large, time-varying dynamic parameters, which fluctuate based on operating conditions, specifically as the electrode weight changes within its operational range. The system identification methodology for robust control is developed in four main steps, progressing from experimental design to model validation. This approach yields a nominal model of the actual system and provides a trustworthy estimate of the region of uncertainty of the model, bounded by models of the real system under maximum and minimum electrode weight conditions (limit operating models). The methodology generates three fourth-order time-delay models using an ARMAX structure. The results are promising, as system identification for robust control enables the derivation of mathematical models specifically tailored for designing robust controllers. These controllers significantly enhance the EPS control system’s performance and substantially reduce energy consumption and environmental emissions.

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Electric Arc Furnace Electrode Movement Control System Based on a Fuzzy Arc Length Identifier

Cited by 3 publications

References 27 publications

Increasing the Level of Autonomy of Control of the Electric Arc Furnace by Weakening Interphase Interactions

Increasing the Level of Autonomy of Control of the Electric Arc Furnace by Weakening Interphase Interactions

Fuzzy Logic Controller for Power Control of an Electric Arc Furnace

System Identification for Robust Control of an Electrode Positioning System of an Industrial Electric Arc Melting Furnace

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