Applying Model Predictive Control to Dividing Wall Columns

Abstract

The technology of dividing wall columns can offer enormous energy savings compared to common distillation columns and configurations. The technology of model predictive control is also advantageous since such a controller minimizes the future deviation of the predicted controlled variable from the reference point. The practical application of model predictive controllers for dividing wall columns is still limited due to limited experience with high interactions among the process variables. The scope of this work is the development and analysis of a method for the design of model predictive controllers for dividing wall columns. An experimental investigation verifies the practicability of the applied approach. The methods generated are transferable to other applications. Thus, the industrial acceptance of model predictive controllers for dividing wall columns is enhanced.

Modeling and model predictive control of dividing wall column for separation of Benzene–Toluene-o-Xylene

“…(Backx, Bosgra, & Marquardt, 2000;De Temmerman, Dufour, Nicolaï, & Ramon, 2009). In view of the multi-input-multi-output system, the MPC is characterized by many manipulated and controlled variables and it may be performed for a complex system (Buck et al, 2011). It is an appropriate controller to control a multivariable process with considerable interactions.…”

“…Recently, Buck, Hiller, and Fieg (2011) also reported experimentally, temperature profile of the column by implementing MPC. Their study proves the real-life practicability of MPC; they did not provide an analysis of the transient behavior of DWC under desired disturbances.…”

Experimental Investigation of Decentralized Process Control for Reactive Dividing‐Wall Columns

“…From the industrial point of view a safe operation and stable product quality are essential for a successful implementation. While control concepts are available for reactive distillation [13,14] and non-reactive dividingwall columns [2,15,16], only little information is existing on the control of RDWCs. Most of the published works on RDWC control investigate the closed-loop behavior with mathematical models built in Aspen Dynamics [17][18][19][20][21][22][23][24].…”

Dynamic Matrix Control of a Bubble‐Column Reactor for Microbial Synthesis Gas Fermentation

“…Over the past four decades, model predictive control schemes such as dynamic matrix control (DMC) have become firmly established in the refinery and commodity chemical industries due to their ability to handle multivariable processes, variable constraints, slow response times, and time delays [22,23]. DMC involves the online solution of a quadratic programming problem [24,25], providing considerable flexibility compared to traditional proportional integral derivative (PID) control [26,27].…”