Application of Soft Constrained MPC to a Cement Mill Circuit

In this paper we develop a Model Predictive Controller (MPC) for regulation of a cement mill circuit. The MPC uses soft constraints (soft MPC) to robustly address the large uncertainties present in models that can be identified for cement mill circuits. The uncertainties in the linear predictive model of the cement mill circuit stems from large variations and heterogeneities in the feed material as well as operational variations. These sources of variations give rise to very nonlinear behavior and variations in the dead-times of the cement mill circuit. The uncertainties may be characterized by the gains, time constants, and time delays in a transfer function model. The developed soft MPC is compared to a normal MPC. The comparison is conducted using a rigorous cement mill circuit simulator used for operator training. The simulations reveal that compared to normal MPC, soft MPC regulate cement mill circuits better and in a plant friendly way by using less variations in the manipulated variables (MVs).