Autogenous grinding is characterized by non-linearities, time-varying
dynamics and a high level of uncertainties, conditions which usually o
riginate from the variability of the ore feed characteristics (hardnes
s and grade). These characteristics make this grinding operation parti
cularly appealing for some type of knowledge-based control. This paper
discusses the application of the dynamic matrix control algorithm to
an autogenous grinding operation. This control algorithm is a long-ran
ge predictive control algorithm which has been successfully applied to
other processes. The study was carried out using an empirical simulat
or calibrated with industrial data. The simulation results were compar
ed to those obtained using PID and learning controllers. The ability o
f the dynamic matrix control to improve the efficiency of this complex
and highly sensitive process is clearly demonstrated.