Stable operation of grinding plants is of great importance as it ensures improved efficiency and mineral recovery The majority of current control solutions in mineral grinding plants are based largely on expert control systems which aim to maximize throughput while keeping operational variables within predefined safe limits and a stable process operation Nevertheless, these systems are not without disadvantages: they tend to systematize bad operational practices; there are no clear procedures to tune them and they exhibit poor response to unmeasured disturbances Strategies based on predictive control, on the other hand, allow the handling of operational constrains, unmeasured disturbances and coupling of operational variables Additionally, they are comparably easier to tune and are less sensitive to modeling errors This paper presents a comparative analysis of three control strategies applied to a mineral grinding plant The tested controllers are: (i) single centralized MPC, (ii) decentralized MPC for SAG mills and ball mills and (iii) multi-level control with a higher optimization layer and a lower decentralized MPC regulatory layer These three control strategies are implemented using various Honeywell's Profit Suite software applications and the comparative analysis is performed through simulation In order to analyze the strategies, several performance indices are defined Copyright © 2013 IFAC.