A dynamic flotation model for predictive control incorporating froth physics. Part I: Model development

Abstract

Part I introduces a dynamic model of froth flotation designed for model predictive control, the first of its kind to include key froth physics. Accounting for the froth improves estimates of the valuable material and entrained gangue reporting to the concentrate, which can serve as proxies for grade and recovery. The paper includes a sensitivity analysis of the model parameters and simulations of key control variables.

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.