Realtime Digital Computer State Estimator for a Hard Rock Milling Circuit

Abstract This paper describes the development of non-linear stochastic dynamic models of the unit operations in a large, complex milling circuit which are combined to form the basis for building a two-stage extended Kalman filter. The filter provides optimal parameter and state estimates of the operating plant. A description is given of the techniques used for implementing the estimator on a digital computer such that on-line estimates are generated in real time. Sufficient additional real-time computing ability is available to generate control inputs based on the plant estimates. The filter was shown to predict adequately the pebble load in the mills (this is the most useful variable for pebble feed control), water hold-ups, solids hold-ups and particle size distributions around the circuit from measurements of pebble mill power draft, overflow fraction -75 µm and specific gravity, rod mill feed rate and sump discharge specific gravity. The single most important difficulty encountered was the bias introduced by inaccurate modelling of the units and the filter segmentation or “decentralisation” that is necessary because of real-time considerations.