State and Parameter Estimation for a Grinding Mill Circuit from Operational Input-Output Data

Abstract

The states and unknown parameters of a simplified non-linear grinding mill circuit model for process control was estimated from real plant data by means of an Extended Kalman Filter. The output of the model as calculated from the states and parameters estimated by the Extended Kalman Filter closely follow the actual output of the plant. The continuous estimate of states and parameters from plant data allows for the continuous update of a process model used for process control. This limits model-plant mismatch which deteriorates controller performance.