Tecnura (Sep 2013)
Regularización de Tikhonov para estimar los parámetros de un modelo de un horno de arco
Abstract
In this paper, we present a methodology for estimating the parameters of a model for an electrical arc furnace by using Tikhonov regularization. Tikhonov regularization is one of the most widely employed methods for regularization. The model proposed for an electrical arc furnace takes into account the highly nonlinear and time varying characteristic of this type of load. We use Regularization Tools (an open-source Matlab toolbox) to determine the value of an estimated-parameter vector with smaller norms. Results obtained through simulation of the model in PSCAD are compared to real measurements taken during the furnace’s most critical operating point. We present models for the electrical arc furnace with appropriate parameter tuning, capturing the real three-phase voltage at the secondary of a furnace transformer with great detail. Results show a maximum error of 2,8 % when line current’s root mean square error is applied.