Modifier-Adaptation methodology for RTO applied to distillation columns using a simplified steady-state model

Real-Time Optimization (RTO) is not always able to achieve optimal process operation due to different reasons, among them the presence of significant uncertainty in the plant models that are used to make decisions or the differences between control architecture layers which operate at different time-scales and use different kind of models. To overcome these issues the economic optimization problem, solved in the RTO layer, is modified following the Modifier Adaptation methodology (MA) to bring the process to the real optimum despite the presence of uncertainty by using plant measurements. This paper presents the implementation of MA methodology to the optimal management of distillation columns as a depropanizer column. Specifically, two approaches have been implemented starting from the traditional gradient-based technique called Dual Modifier Adaptation (DMA) to the recent approach Nested Modifier Adaptation (NMA), updating modifiers at the steady state of the process using static information. The RTO layer is based on a really simplified static model of the process which implies the presence of strong structural plant-model mismatch.