Model-plant mismatch detection and model update for a run-of-mine ore milling circuit under model predictive control
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Date
Authors
Olivier, Laurentz Eugene
Craig, Ian Keith
Journal Title
Journal ISSN
Volume Title
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.
Description
Keywords
Milling circuit, Model-plant mismatch, Model predictive control, Run-of-mine (ROM) ore
Sustainable Development Goals
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.