Dynamic physics-based flotation models for effective predictive control
Creators: name: Quintanilla, Paulina
Publisher: name: Imperial College London
Year: 2022

description: Flotation is arguably the most important mineral separation technique. It is a multiphase process that exhibits inherent instabilities, and thus complex dynamics. One of the most efficient ways to increase flotation performance is by implementing advanced controllers, such as Model Predictive Control (MPC). The effectiveness of MPC strategies relies on the model that represents the dynamics of the process, which has often hindered its application in froth flotation. Previous studies of MPC implementation in flotation have primarily used kinetic models to phenomenologically represent the attachment-detachment of mineral particles in the pulp phase. While kinetic models can adequately represent the phenomena in the pulp phase, they are not suitable to model the complex phenomena in the froth phase. This is particularly relevant since froth phase phenomena are key drivers of froth performance and yet are often neglected in flotation models. This study presents the development and implementation of a novel dynamic flotation model that incorporates froth physics and is thus suitable for MPC. Unlike other flotation models for control in the literature, the model proposed here includes, for the first time, important variables related to froth stability, such as bursting rate and air recovery, as well as simplified phenomenological equations to calculate froth recovery and entrainment. The model also incorporates pulp-froth interface physics, which enables a more accurate prediction of relevant flotation variables. The model was experimentally calibrated and validated with measurements of the variables of interest in a large laboratory-scale flotation cell. Subsequent simulations validated model predictions against experimental data, with excellent agreement obtained for important flotation variables, such as pulp level, air recovery, and overflowing froth velocity. The high accuracy of the predictions suggested that the model can be successfully used for predictive control strategies. A novel economic model predictive control (E-MPC) strategy was developed using the proposed dynamic model for both a single froth flotation cell and a flotation bank. Particularly for the flotation bank, a centralised E-MPC strategy was developed so that a global optimum is ensured. The E-MPC strategies were implemented in both simulations and a laboratory-scale flotation rig. The simulation results of the E-MPC strategies revealed significant improvements in metallurgical recovery in all cases, maintaining the concentrate grade at 20% as a minimum. E-MPC implementation in the laboratory-scale flotation rig also improved recoveries, although challenges in convergence for flotation bank control, primarily caused by the high computational demand of the centralised system, were identified. Further work is therefore discussed in this thesis to include algorithms that are less computationally demanding. Implementing the predictive control strategy has nevertheless provided encouraging results, demonstrating the model's potential for integration into a larger flotation control system.