Model based predictive control of a rougher flotation circuit considering grade estimation in intermediate cells.

Abstract

Effective control of rougher flotation is important because a small increase in recovery results in a significant economic benefit. Although many flotation control strategies have been proposed and implemented over the years, none of them incorporate concentrate grade measurements at intermediate cells because these data are not usually available. On the other hand, there is much research on characterizing concentrate froth on the cell surface by image processing in order to extract information on froth color, bubble size, and speed that can then be used for developing expert control strategies, and some works have shown the possibility of estimating the concentrate grade. This work presents two multivariable model based predictive control (MPC) strategies for a rougher circuit. The first strategy is based only on general tailings and concentrate grade measurements while the second one includes, beside these data, the intermediate cell grade estimates. Both strategies are compared with a fixed control strategy. Simulation tests show that the recovery can increase by 1.7%, compared to the fixed control strategy.