Enhanced grinding process of a cement ball mill through a generalised predictive controller integrated with a CARIMA model

Cement ball mills in the finishing stage of the cement industries consume the highest energy in the cement manufacturing stage. Therefore, suitable controllers that result in good productivity and product quality with reduced energy consumption are required for the cement ball mill grinding process to increase the profit margins. In this study, generalised predictive controllers (GPC)have been designed for the cement ball mill grinding operation using the model obtained from the step response data taken from the industrially recognized simulator. The servo and regulatory responses are analysed with and without constraints by implementing the designed GPC under the closed loop. The error metrics for GPC and conventional controllers are also analysed. The designed GPC for the cement ball mill grinding process outperforms the traditional controller in error metrics.

Authors

Institutions

Publication Details

Journal
Scientific Reports
Published
2024-12-28
DOI
https://doi.org/10.1038/s41598-024-82708-w
Citations
2
Primary Topic
Mineral Processing and Grinding
Type
article
Field-Weighted Citation Impact
0.43

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Enhanced grinding process of a cement ball mill through a generalised predictive controller integrated with a CARIMA model

Rengarajan Amirtharajan, K. Ramkumar, Hemalatha Mahalingam, S. Venkatesh et al.
2 citations
Scientific Reports
Mineral Processing and Grinding
0.43
article

Enhanced grinding process of a cement ball mill through a generalised predictive controller integrated with a CARIMA model

Rengarajan Amirtharajan, K. Ramkumar, Hemalatha Mahalingam, S. Venkatesh, R. Valarmathi, Gomathi Veerasamy
article en
2 citations

Abstract

Cement ball mills in the finishing stage of the cement industries consume the highest energy in the cement manufacturing stage. Therefore, suitable controllers that result in good productivity and product quality with reduced energy consumption are required for the cement ball mill grinding process to increase the profit margins. In this study, generalised predictive controllers (GPC)have been designed for the cement ball mill grinding operation using the model obtained from the step response data taken from the industrially recognized simulator. The servo and regulatory responses are analysed with and without constraints by implementing the designed GPC under the closed loop. The error metrics for GPC and conventional controllers are also analysed. The designed GPC for the cement ball mill grinding process outperforms the traditional controller in error metrics.

Scientific ReportsVol. 14(1)
King Abdulaziz University (SA), Indian Institute of Technology Madras (IN), Anna University, Chennai (IN), SASTRA University (IN)
King Abdulaziz University
Openalex Percentile: Top 40%
Mineral Processing and Grinding
0.43
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.