Sequential control performance diagnosis of steel processes

Tools

Recalde, L.F. and Katebi, R. and Yue, H. (2014) Sequential control performance diagnosis of steel processes. IFAC Proceedings Volumes, 47 (3). 2830 – 2835. ISSN 1474-6670 (https://doi.org/10.3182/20140824-6-ZA-1003.00557)

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Abstract

A sequential method for Control Performance Diagnosis using a classication tree to predict possible root-causes of poor performance is presented. The classication tree methodology is used to combine process pre-assessment (nonlinearities detection, delays estimation and controller assessment), Control Performance Assessment (CPA) and ANalysis Of VAriance (ANOVA) into an integrated framework. A initial process data set is analysed and the results are used as decision thresholds for the classication tree. The methodology is capable to identify root-causes such as:poor tuning, inadequate control structure, nonlinearities, process mismatch and disturbance changes. The proposed methodology is applied to individual loops of a tandem cold rolling mill.

ORCID iDs

Recalde, L.F. ORCID logoORCID: https://orcid.org/0000-0002-3911-2857, Katebi, R. ORCID logoORCID: https://orcid.org/0000-0003-2729-0688 and Yue, H. ORCID logoORCID: https://orcid.org/0000-0003-2072-6223;
CORE (COnnecting REpositories)