INTEGRATING REAL TIME OPTIMIZATION AND MODEL PREDICTIVE CONTROL OF A CRUDE DISTILLATION UNIT

Abstract This work reports the integration of Real Time Optimization and Model Predictive Control in the multi-layer control structure of an existing Crude Distillation Unit (CDU) of an oil refinery. The MPC considers output control zones and targets for the inputs or outputs. Both the infinite horizon and the finite output horizon controllers were tested. The plant results show that the infinite horizon controller tends to perform similarly or better then the finite horizon MPC when the CDU system needs to operate at quite different conditions. Although the dynamic layer based on the infinite horizon controller is nominally stable for any set of tuning parameters, in practice, it is observed that the interaction between the layers of the control structure associated to model uncertainty may result in oscillations in some variables that fail to converge to the optimum operation point. This problem can be solved with the retuning of the intermediary layer (target calculation layer), which indicates that the frequent tuning of the MPC is recommended and should be performed in conjunction with tuning of the intermediary layer.