TY - GEN
T1 - Effect of Variations of Delays and Sensitivities in the Predictive Control MPC-GPC Applied to the Grinding in Mineral Concentrating Plant
AU - Tisza, Juan
AU - Ortega, David
N1 - Publisher Copyright:
© 2020 IEEE.
Copyright:
Copyright 2020 Elsevier B.V., All rights reserved.
PY - 2020/9
Y1 - 2020/9
N2 - In mining, the particle size obtained after grinding greatly influences the amount of mineral recovered, so to obtain an efficient operation with a reduction in production cost, the grinding circuit must have optimal control, however, the system is complex and has many input and output variables that interact with each other. This paper uses a 4x4 MIMO model that has been obtained by an experimental process and implements a model-based predictive control strategy (MPC) in the generalized predictive control (GPC) modality, with optimal control characteristics. The objective is to investigate the effect that occurs on the control due to degradations of the components of the grinding process, which is reflected in changes in the delays and the sensitivity of the transfer functions. The effects on control are evaluated in parameters such as overshoot, rise time, and disturbances in controlled variables caused by variations in delays and amplitudes in the transfer functions of the model. The effects presented and analyzed in the results section provide considerations that are of interest for tuning the control system, it also provides important criteria for plant operation and maintenance. The results have been obtained by simulation with Matlab.
AB - In mining, the particle size obtained after grinding greatly influences the amount of mineral recovered, so to obtain an efficient operation with a reduction in production cost, the grinding circuit must have optimal control, however, the system is complex and has many input and output variables that interact with each other. This paper uses a 4x4 MIMO model that has been obtained by an experimental process and implements a model-based predictive control strategy (MPC) in the generalized predictive control (GPC) modality, with optimal control characteristics. The objective is to investigate the effect that occurs on the control due to degradations of the components of the grinding process, which is reflected in changes in the delays and the sensitivity of the transfer functions. The effects on control are evaluated in parameters such as overshoot, rise time, and disturbances in controlled variables caused by variations in delays and amplitudes in the transfer functions of the model. The effects presented and analyzed in the results section provide considerations that are of interest for tuning the control system, it also provides important criteria for plant operation and maintenance. The results have been obtained by simulation with Matlab.
KW - generalized predictive control (GPC)
KW - Grinding circuit
KW - MIMO control
KW - model-based predictive control (MPC)
UR - http://www.scopus.com/inward/record.url?scp=85095436976&partnerID=8YFLogxK
U2 - 10.1109/INTERCON50315.2020.9220268
DO - 10.1109/INTERCON50315.2020.9220268
M3 - Contribución a la conferencia
AN - SCOPUS:85095436976
T3 - Proceedings of the 2020 IEEE 27th International Conference on Electronics, Electrical Engineering and Computing, INTERCON 2020
BT - Proceedings of the 2020 IEEE 27th International Conference on Electronics, Electrical Engineering and Computing, INTERCON 2020
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 27th IEEE International Conference on Electronics, Electrical Engineering and Computing, INTERCON 2020
Y2 - 3 September 2020 through 5 September 2020
ER -
