Abstract:
Autogenous (AG) milling is utilised around the world for particle size reduction. The system exhibits
highly non-linear behaviour in addition to being subject to unmeasured variability associated with most
ore bodies. Anglo American Platinum aimed at improving online optimisation of the circuit by implementing
industrial model predictive control (MPC) to reduce system variability and continuously drive
towards the optimal operating point within system constraints.
The industrial dynamic matrix controller commissioned on the AG mill with a variable speed drive
resulted in a 66% reduction in power and a 40% reduction in load standard deviation. These are the main
controlled variables of the mill. The controller also improved the objective function, effective power utilisation,
by 11%. This reduction in operated variable variability enabled a test campaign where the mill
was controlled at various operating regions in order to establish the conditions conducive to the finest
product size at a given mill feed rate.
Moving the mill operating region from the benchmarked plant to the optimal grind environment and
stabilising the mill at this point with the model predictive controller provided an estimated potential
recovery increase of 0.32% (absolute) due to better liberation.
