Economic model predictive control for a rougher froth flotation cell using physics-based models
Abstract
An economic model predictive control (E-MPC) strategy for a rougher flotation cell, built on a dynamic model that includes froth physics. Including air recovery (measurable online) and concentrate grade dynamics in the objective gave the best results, with a minimum grade enforced as an economic constraint. Using laboratory-scale data, the strategy improved metallurgical recovery by 8–22% while maintaining the target grade.
Type
Publication
Minerals Engineering
Dr Paulina Quintanilla
Assistant Professor in Process Systems Engineering
Assistant Professor in Process Systems Engineering at UCL, leading the LOOPS research group. Research interests include machine learning, optimisation and control for processes and physical systems.