HYBRID NON-LINEAR MODEL PREDICTIVE CONTROL OF A RUN-OF-MINE ORE

A run-of-mine (ROM) ore milling circuit is primarily used to grind incoming ore containing precious metals to a powder fine enough to liberate the valuable minerals contained therein. The ground ore has a product particle size specification that is set by the downstream separation unit. However, controlling a ROM ore milling circuit has challenges due to unmeasurable process outputs, non-linearities, time delays, and large unmeasured disturbances. This study investigates hybrid non-linear model predictive control (MPC) in order to optimize throughput while meeting the final product quality specification, which often presents an inverse relationship. By integrating additional manipulated variables within the MPC framework, the study aimed to enhance control performance in this complex environment. The proposed methodology was assessed through simulations that mimicked real-world conditions encountered in milling circuits. Results indicated that the hybrid MPC approach outperformed traditional control methods by accommodating process disturbances more effectively and achieving superior product quality. The findings suggest that continued development of control strategies is essential to meet evolving challenges in ROM ore grinding mill circuit control. A deeper understanding of process dynamics could lead to more robust control solutions for industrial applications.