A mill is a mechanical device that grinds mined or processed material into
small particles. The process is known to display significant deadtime, and,
more notably, severe nonlinear behavior. Over the past 25 years attempts a
t continuous mill control have met varying degrees of failure, mainly due t
o model mismatch caused by changes in the mill process gains. This paper de
scribes an on-line control application on a closed-circuit cement mill that
uses nonlinear model predictive control technology. The nonlinear gains fo
r the control model are calculated on-line from a neural network model of t
he process. (C) 2001 Elsevier Science Ltd. All rights reserved.