Regularización de Tikhonov para estimar los parámetros de un modelo de un horno de arco

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...

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Bibliographic Details
Main Authors: Jesser James Marulanda Durango, Alfonso Alzate Gómez, Christian David Sepúlveda Londoño, Mauricio Holguín Londoño
Format: Article
Language:Spanish
Published: Universidad Distrital Francisco Jose de Caldas 2013-09-01
Series:Tecnura
Subjects:
Online Access:http://tecnura.udistrital.edu.co/ojs/index.php/revista/article/view/626/560
Description
Summary: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.
ISSN:0123-921X
2248-7638