Modifier-Adaptation Based on Transient Measurements Applied to a Laboratory-Scale Flotation Column

Abstract

Real-Time Optimization (RTO) is not always able to achieve optimal process operation due to the presence of significant uncertainty. To overcome this issue, the economic optimization problem is modified following the Modifier-Adaptation methodology (MA) to bring the process to a point that satisfies the necessary optimality conditions (NCO) despite the presence of uncertainty. Traditionally, modifiers are updated only at the steady state using static information. This may imply a slow convergence of MA, or undesired interactions with side units. This issue is considered in this paper, where a transient-based methodology (TMA) is applied to estimate the modifiers in a laboratory-scale flotation column for copper concentration. As flotation columns interact with up and down stream units, waiting several steady states to find the optimum of the process can produce undesired effects. Experimental results show that TMA allows saving 10 steady states to find a point that satisfies the NCO of the process which is translated into a 64% reduction in time compared to dual MA (DMA).