<?xml version="1.0" encoding="ISO-8859-1"?><article xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance">
<front>
<journal-meta>
<journal-id>1815-5928</journal-id>
<journal-title><![CDATA[Ingeniería Electrónica, Automática y Comunicaciones]]></journal-title>
<abbrev-journal-title><![CDATA[EAC]]></abbrev-journal-title>
<issn>1815-5928</issn>
<publisher>
<publisher-name><![CDATA[Universidad Tecnológica de La Habana José Antonio Echeverría, Cujae]]></publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id>S1815-59282022000300015</article-id>
<title-group>
<article-title xml:lang="es"><![CDATA[Modelo NARX de la postcombustión en un horno de reducción de mineral laterítico]]></article-title>
<article-title xml:lang="en"><![CDATA[NARX model of post-combustion in a lateritic ore reduction furnace]]></article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Montero Góngora]]></surname>
<given-names><![CDATA[Deynier]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Columbié Navarro]]></surname>
<given-names><![CDATA[Ángel Oscar]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Montero Laurencio]]></surname>
<given-names><![CDATA[Reineris]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Trujillo Codorniú]]></surname>
<given-names><![CDATA[Rafael Arturo]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Vázquez Seisdedos]]></surname>
<given-names><![CDATA[Luis]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
</contrib-group>
<aff id="Af1">
<institution><![CDATA[,Universidad de Moa  ]]></institution>
<addr-line><![CDATA[Holguín ]]></addr-line>
<country>Cuba</country>
</aff>
<aff id="Af2">
<institution><![CDATA[,Universidad de Oriente  ]]></institution>
<addr-line><![CDATA[Santiago de Cuba ]]></addr-line>
<country>Cuba</country>
</aff>
<pub-date pub-type="pub">
<day>00</day>
<month>12</month>
<year>2022</year>
</pub-date>
<pub-date pub-type="epub">
<day>00</day>
<month>12</month>
<year>2022</year>
</pub-date>
<volume>43</volume>
<numero>3</numero>
<fpage>15</fpage>
<lpage>28</lpage>
<copyright-statement/>
<copyright-year/>
<self-uri xlink:href="http://scielo.sld.cu/scielo.php?script=sci_arttext&amp;pid=S1815-59282022000300015&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://scielo.sld.cu/scielo.php?script=sci_abstract&amp;pid=S1815-59282022000300015&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://scielo.sld.cu/scielo.php?script=sci_pdf&amp;pid=S1815-59282022000300015&amp;lng=en&amp;nrm=iso"></self-uri><abstract abstract-type="short" xml:lang="es"><p><![CDATA[RESUMEN La Empresa Productora de Níquel y Cobalto &#8220;Comandante Ernesto Che Guevara&#8221; desempeña un rol esencial en el desarrollo económico de Cuba. Dentro del proceso productivo de la industria, el horno de reducción de mineral laterítico es una etapa clave y requiere un alto consumo de fuel oil, que representa alrededor del 40 % del costo unitario por tonelada producida de níquel más cobalto, por lo que resulta vital reducir tales costos. La implementación del sistema de control automático en la postcombustión se ha visto afectada por no disponer de modelos matemáticos de este proceso. En la presente investigación se propone un modelo de caja negra basado en redes neuronales artificiales que refleja las características dinámicas del proceso. La metodología empleada consta de la realización de experimentos pasivos de 10 meses de operación para la confección de un algoritmo recurrente que incluye los métodos de validación cruzada aleatoria y el criterio de información de Akaike. Como resultado se obtuvo un modelo NARX (estructura no lineal autorregresiva con entradas externas) que predice las temperaturas de los hogares cuatro y seis del horno, obteniendo un error cuadrático medio inferior a 5 °C, con un horizonte de predicción de un paso adelante (120 s). La exactitud lograda con el modelo contribuye a predecir el perfil térmico en la zona de calentamiento del horno, como base para el diseño de estrategias de control que garanticen un mejor aprovechamiento de la energía y del combustible aditivo reductor, que permitiría disminuir las pérdidas del proceso y la contaminación ambiental.]]></p></abstract>
<abstract abstract-type="short" xml:lang="en"><p><![CDATA[ABSTRACT The Nickel and Cobalt Production Company "Comandante Ernesto Che Guevara" plays an essential role in the economic development of Cuba. Within the industrial production process, the lateritic ore reduction furnace is a key stage and requires a high consumption of fuel oil, which represents around 40% of the unit cost per ton produced of nickel plus cobalt, making it vital. reduce such costs. The implementation of the automatic control system in post-combustion has been affected by not having mathematical models of this process. In the present investigation, a black box model based on artificial neural networks that reflects the dynamic characteristics of the process is proposed. The methodology used consists of carrying out passive experiments of 10-months operating time period for the preparation of a recurrent algorithm that includes the methods of random cross validation and the Akaike&#8217;s information criterion. As a result, a NARX model (non-linear autoregressive structure with external inputs) was obtained that predicts the temperatures of hearths four and six, obtaining a mean square error of less than 5 °C, with a prediction horizon one step ahead (120s). The accuracy achieved with the model contributes to predicting the thermal profile in the heating zone of the furnace, as a basis for the design of control strategies that guarantee a better use of energy and of the reducing additive fuel, which would reduce process losses. and environmental pollution.]]></p></abstract>
<kwd-group>
<kwd lng="es"><![CDATA[horno de reducción]]></kwd>
<kwd lng="es"><![CDATA[postcombustión]]></kwd>
<kwd lng="es"><![CDATA[modelo NARX]]></kwd>
<kwd lng="es"><![CDATA[validación cruzada aleatoria]]></kwd>
<kwd lng="es"><![CDATA[criterio de información de Akaike]]></kwd>
<kwd lng="en"><![CDATA[reduction furnace]]></kwd>
<kwd lng="en"><![CDATA[post-combustion]]></kwd>
<kwd lng="en"><![CDATA[NARX model]]></kwd>
<kwd lng="en"><![CDATA[random cross-validation]]></kwd>
<kwd lng="en"><![CDATA[Akaike´s information criteria]]></kwd>
</kwd-group>
</article-meta>
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