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通过与CARIMA模型集成的广义预测控制器对水泥球磨机进行强化粉磨工艺

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

作者信息

Sivanandam Venkatesh, Kannan Ramkumar, Ramasamy Valarmathi, Veerasamy Gomathi, Mahalingam Hemalatha, Amirtharajan Rengarajan

机构信息

School of Electrical & Electronics Engineering, SASTRA Deemed University, Thanjavur, 613 401, India.

School of Computing, SASTRA Deemed University, Thanjavur, 613 401, India.

出版信息

Sci Rep. 2024 Dec 28;14(1):31317. doi: 10.1038/s41598-024-82708-w.

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.

摘要

水泥行业粉磨阶段的水泥球磨机在水泥制造阶段能耗最高。因此,水泥球磨机粉磨过程需要合适的控制器,以在降低能耗的同时实现良好的生产率和产品质量,从而提高利润率。在本研究中,利用从工业认可的模拟器获取的阶跃响应数据得到的模型,为水泥球磨机粉磨操作设计了广义预测控制器(GPC)。通过在闭环条件下实施所设计的GPC,分析了有无约束情况下的伺服响应和调节响应。还分析了GPC与传统控制器的误差指标。所设计的用于水泥球磨机粉磨过程的GPC在误差指标方面优于传统控制器。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6f3a/11682061/d5ea2c99f8d8/41598_2024_82708_Fig1_HTML.jpg

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