Experimental implementation of an economic model predictive control for froth flotation

TL;DR

This paper demonstrates a novel economic model predictive control strategy for froth flotation, significantly improving mineral recovery in a laboratory setting by leveraging a detailed dynamic model and advanced optimization techniques.

Contribution

It introduces an innovative E-MPC approach using orthogonal collocation and CasADi for froth flotation control, overcoming previous model simplifications.

Findings

Mineral recovery increased from 9% to 29%.

Control maintained a concentrate grade of at least 20%.

The method effectively handled feed flowrate disturbances.

Abstract

We present the implementation of a novel economic model predictive control (E-MPC) strategy for froth flotation, the largest tonnage mineral separation process. A previously calibrated and validated dynamic model incorporating froth physics was used, which overcomes the limitations of previous simplified models reported in the literature. The E-MPC's optimal control problem was solved using full discretization with orthogonal collocation over finite elements, employing automatic differentiation via CasADi. This approach was applied in a 30-litre laboratory-scale flotation cell, significantly improving mineral recovery from 9% to 29% under feed flowrate disturbances while maintaining a minimum concentrate grade of 20%.