Abstract
This paper presents a new application of a genetic-fuzzy control system which controls the input energy to a three phase electric arc furnace. Graphite electrodes are used to convert electrical energy into heat via phase electric arcs. Con-stant arc length is desirable as it implies steady energy transfer from the graphite electrodes to the metallic charge in the furnace bath. With the charge level constantly changing, the electrodes must be able to adjust for the arc length to remain constant. A fuzzy PI controller tuned with genetic algorithms has been developed to be responsible for the ver-tical adjustment of the electrode tip displacement according to specified set-points to ensure that the arc lengths remain as constant as possible. The simulation results show that the system performances are satisfactory using the proposed method.
Highlights
The production of steel by Electric Arc Furnaces (EAF) has steadily expanded during the past few decades
This paper presents a new application of a genetic-fuzzy control system which controls the input energy to a three phase electric arc furnace
The graphite electrodes connected to the electrical supply are used to convert electrical energy into extensive heat by means of high current electric arcs drawn between the electrode rips and the metallic charge [2]
Summary
The production of steel by Electric Arc Furnaces (EAF) has steadily expanded during the past few decades. A modeling approach using a time domain controlled voltage source is presented in [12] This model is based on a piece-wise linear approximation of the v–i characteristic of the arc furnace load. A model using parametric system identification techniques is presented in [20] This method used data collected from an operating EAF and both AR (auto regression) and ARX (auto regression with auxiliary input) models to explain the dynamics of electric arc furnaces [36].
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