Controlled high pressure grinding roll by model predictive control

High Pressure Grinding Rolls (HPGR) technology has been considered as an alternative in the mining industry. This consideration has been given by its energy efficient characteristics (i.e. lower energy consumption compared to other types of technologies. such as semiautogenous technologies). Mathematical models that describe the behavior of this equipment are used to evaluate and predict yields (in terms of granulometric distribution), nevertheless their use and consideration for control processes is scarce. The present work focuses in the development of a dynamic representation of a HPGR unit, and the control of it, by considering a first order kinetic representation of the grinding process and the total energy consumed by the HPGR as the main controlled variable. The model considers a dynamic evaluation of the rolls peripheral velocity, the operational gap, and the feed mass flow as manipulated variables (the first two can be directly correlated to energy) while the density in the extrusion zone and the 80% size percentile were selected as the controlled variables. As result, it was observed that the model has a correct representation of the phenomena involved and that the selected variables are useful manipulated variables to control the energy consumed by the equipment.