Pe. King et Md. Nyman, MODELING AND CONTROL OF AN ELECTRIC-ARC FURNACE USING A FEEDFORWARD ARTIFICIAL NEURAL-NETWORK, Journal of applied physics, 80(3), 1996, pp. 1872-1877
Previous studies have shown that the electric arc furnace is chaotic i
n nature and hence standard control techniques are not effective. Howe
ver, human (heuristic) control is used every day on electric arc furna
ces. A furnace operator assesses the performance of the furnace and ma
kes judgments based on past experience and intuition. In order to impr
ove the effectiveness of this control, a qualitative understanding of
the operating conditions of the furnace is required. Artificial neural
networks are capable of learning the system dynamics of the electric
arc furnace. This article describes a feedforward neural network train
ed to model arc furnace electrical wave forms taken from an experiment
al arc furnace. The output of this model is then used in estimating th
e future state of the furnace for control purposes.