Model-plant mismatch detection and model update for a run-of-mine ore milling circuit under model predictive control

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Authors

Olivier, Laurentz Eugene
Craig, Ian Keith

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Publisher

Elsevier

Abstract

The performance of a model predictive controller depends on the quality of the plant model that is available. Often parameters in a run-of-mine (ROM) ore milling circuit are uncertain and inaccurate parameter estimation leads to a mismatch between the model and the actual plant. Although model-plant mismatch is inevitable, timely detection of significant mismatch is desirable. Once significant mismatch is detected the model may be partially re-identified in order to prevent deteriorated control performance. This paper presents a simulation study of the detection of mismatch in the parameters of a ROM ore milling circuit model using a partial correlation analysis approach. The location of the mismatch in the MIMO model matrix is correctly detected, and the process model subsequently updated.

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Keywords

Milling circuit, Model-plant mismatch, Model predictive control, Run-of-mine (ROM) ore

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Citation

Olivier, LE & Craig, IK 2013, 'Model-plant mismatch detection and model update for a run-of-mine ore milling circuit under model predictive control', Journal of Process Control, vol. 23, no. 2, pp. 100-107.