Real-time optimization for a laboratory-scale flotation column

• Real time optimization implemented in a laboratory scale flotation column.
• Optimal recovery and concentration for cleaning units in copper concentration process.
• Comparison of the performance of real time optimization methods in a real system.
• Uncertainty from the standpoint of modeling mismatch and control layer performance.
• Model adequacy as a consequence of the KKT update for experimental uncertainties.

In this paper, a supervisory layer with real-time optimization (RTO) has been implemented in an experimental laboratory-scale flotation column for copper concentration. A two-stage and modifier adaptation (MA) methodology for RTO has been compared under structural, experimental and dynamic uncertainty. In addition, a gradient-free alternative for MA, called nested modifier optimization, has been proposed and tested. The results show that the KKT updates of the MA approach allow the process optimum to be determined under uncertain scenarios, unlike the two-stage approach. From the perspective of gradient modifiers, the performance of the nested methodology is comparable to the dual approach because previous past values are used to update the modifiers without requiring the gradient estimation step. In addition, the interaction of RTO with the regulatory layer must be considered to propose an optimal implementation.