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Título : Predictive control of a closed grinding circuit system in cement industry
Autor: Minchala Avila, Luis Ismael
Zhang, Youmin
Garza Castañón, Luis Eduardo
Correspondencia: Zhang, Youmin, youmin.zhang@concordia.ca
Palabras clave : Integrated circuit modeling
Particle separators
Hidden markov models
Feeds
Markov processes
Process control
Scada systems
Area de conocimiento FRASCATI amplio: 2. Ingeniería y Tecnología
Area de conocimiento FRASCATI detallado: 2.2.2 Robótica y Control Automático
Area de conocimiento FRASCATI específico: 2.2 Ingenierias Eléctrica, Electrónica e Información
Area de conocimiento UNESCO amplio: 07 - Ingeniería, Industria y Construcción
Area de conocimiento UNESCO detallado: 0714 - Electrónica y Automatización
Area de conocimiento UNESCO específico: 071 - Ingeniería y Profesiones Afines
Fecha de publicación : 2018
Fecha de fin de embargo: 30-dic-2050
Volumen: volumen 65, número 5
Fuente: IEEE Transactions on Industrial Electronics
metadata.dc.identifier.doi: 10.1109/TIE.2017.2762635
Tipo: ARTÍCULO
Abstract: 
This paper presents the development of a nonlinear model predictive controller (NMPC) applied to a closed grinding circuit system in the cement industry. A Markov chain model is used to characterize the cement grinding circuit by modeling the ball mill and the centrifugal dust separator. The probability matrices of the Markovian model are obtained through a combination of comminution principles and experimental data obtained from the particle size distribution of cement samples at specific stages of the system. The NMPC is designed as a supervisory controller to manage distributed controllers installed in the process. Both the model and the controller are validated online through the implementation of the proposed approach in the supervisory control and data acquisition (SCADA) system of an industrial plant. The results show a significant improvement in the performance of the grinding circuit in comparison to the operation of the system without the proposed controller.
Resumen : 
This paper presents the development of a nonlinear model predictive controller (NMPC) applied to a closed grinding circuit system in the cement industry. A Markov chain model is used to characterize the cement grinding circuit by modeling the ball mill and the centrifugal dust separator. The probability matrices of the Markovian model are obtained through a combination of comminution principles and experimental data obtained from the particle size distribution of cement samples at specific stages of the system. The NMPC is designed as a supervisory controller to manage distributed controllers installed in the process. Both the model and the controller are validated online through the implementation of the proposed approach in the supervisory control and data acquisition (SCADA) system of an industrial plant. The results show a significant improvement in the performance of the grinding circuit in comparison to the operation of the system without the proposed controller.
URI : https://ieeexplore.ieee.org/document/8066385
URI Fuente: https://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=41
ISSN : 02780046
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