On multi-objective economic predictive control for cyclic process operation

In recent literature, a utopia-tracking strategy has been proposed for multi-objective model predictive control. This strategy tracks a vector of independently minimized objectives, evaluated at steady-state operation (the utopia point). The approach in the present work is based on the premise that cyclic process operation may in some cases outperform, on average, steady-state operation. We therefore concern ourselves with optimizing average performance for one cyclic period of operation. A dynamic utopia-tracking strategy is proposed, which generalizes steady-state utopia-tracking to systems which are optimally operated cyclically. The proposed control law minimizes the distance of its cost vector to a vector of independently minimized objectives, evaluating average cyclic performance (the dynamic utopia point). Recursive feasibility is established for a cyclic terminal state constraint formulation, however, conditions for stability are not given. The theoretical concepts are illustrated for a simple acetylene hydrogenation case, and a more complex oil production optimization case. The simulation study indicates novel operational insight for the oil production optimization case, by illustrating how simultaneous optimization of two objectives results in cyclic operation with improved performance.