Decentralized control and identified-model predictive control of divided wall columns

As a thermal separation method, distillation is one of the most important separation technologies in the chemical industry. Given its importance, it is no surprise that increasing efforts have been made in reducing its energy inefficiencies. A great deal of research is focused in the design and optimization of the divided-wall column (DWC). Its applications are still reduced due to distrust of its controllability and robustness. Previous references have studied the decentralized control of DWC but still few papers deal about model predictive control (MPC) applied to DWC.In this work we present a decentralized control of both a divided-wall column along with its equivalent MPC schema, both approaches are compared. Instead of building a rigorous model or performing the step test to an existing plant, the MPC model is obtained by identification of a rigorous simulation. An ARX model is demonstrated to represent adequately the DWC column behavior. This approach might be very convenient if plant testing is not available.

► A review of existing control strategies for divided-wall columns is presented.
► Using the dynamic responses of a rigorous dynamic model of the column an ARX model is generated.
► An MPC model for the control of the divided-wall column is obtained using the ARX model.
► A comparison between decentralized and MPC is made.
► Results show MPC superiority over the decentralized control structure.