Economic model predictive control of chemical processes with parameter uncertainty

•A novel robust EMPC algorithm that can compute the stability online was developed.•The algorithm does not contain terminal conditions, fix set points or tracking terms in the stage cost that can reduce the performance.•The algorithm was applied to a simulated example showing that the performance was better than similar formulations.•It was demonstrated that our approach could also adapt parameters and deal with model uncertainty.

This work proposes an EMPC (Economic Model Predictive Control) algorithm that integrates RTO (Real Time Optimization) and EMPC objectives within a single optimization calculation. Robust stability conditions are enforced on line through a set of constraints within the optimization problem.A particular feature of this algorithm is that it constantly calculates a set point with respect to which stability is ensured by the aforementioned constraints while searching for economic optimality over the horizon. In contrast to other algorithms reported in the literature, the proposed algorithm does not require terminal constraints or penalty terms on deviations from fixed set points that may lead to conservatism.Changes in model parameters over time are also compensated for through parameter updating. The latter is accomplished by including the parameters' values as additional decision variables within the optimization problem.Several case studies are presented to demonstrate the algorithm's performance.