Model-plant mismatch diagnosis using plant model ratios for a grinding mill circuit under model predictive control

Abstract

Model-based controllers often extend improved performance to mineral processing plants by leveraging predictive models to account for system dynamics, handling constraints, adapting to changing conditions, and optimizing control inputs. Inaccurate models will cause a deterioration of controller performance, which is often the case for grinding mill circuits. The plant model ratio was developed to diagnose parametric model plant mismatches for first-order plus time delay models. Using a simulation study, the plant model ratio is applied to test the feasibility of using the plant model ratio on a grinding mill circuit. By applying different scenarios of mismatch, some limitations of the plant model ratio are identified and discussed in light of a grinding mill circuit model that is used in model-based controllers. The plant model ratio is capable of identifying parametric model plant mismatches for the model of a grinding mill circuit, specifically changes in the direction of responses. This may occur in cases where disturbances push a grinding mill to operate to the right of the peak of a grind curve.

HIGHLIGHTS • Inaccurate process models deteriorate model-based controller performance. • Plant model ratio (PMR) can identify model-plant mismatch (MPM) for MIMO systems. • A simulation study shows how PMR can identify MPM for a grinding mill circuit. • PMR is effective to identify changes in the response direction of process variables.