Optimizing control of simulated moving bed separations of mixtures subject to the generalized Langmuir isotherm

• Published in: Adsorption : journal of the International Adsorption Society Vol. 14; no. 2-3; pp. 423 - 432
• Main Authors: Grossmann, Cristian, Amanullah, Mohammad, Morari, Manfred, Mazzotti, Marco, Morbidelli, Massimo
• Format: Journal Article
• Language: English
• Published: Boston Springer US 01.06.2008
• Subjects: Chemistry; Chemistry and Materials Science; Engineering Thermodynamics; Heat and Mass Transfer; Industrial Chemistry/Chemical Engineering; Surfaces and Interfaces; Thin Films; Multicolumn processes; Preparative chromatography; Liquid phase adsorption
• ISSN: 0929-5607; 1572-8757
• DOI: 10.1007/s10450-007-9083-8

Simulated moving bed (SMB) is a cost-efficient separation technique that offers high productivity and low solvent consumption. SMB has gained importance in the pharmaceutical and fine chemical industry to perform complex separation tasks. However, an open and challenging problem is the optimal, robust operation of the SMB process. We have developed a control scheme that integrates the optimization and control of the SMB unit. A significant feature of the controller is that only minimal information of the system has to be provided, i.e. the linear adsorption behavior of the mixture to be separated and the average void fraction of the columns. Therefore, a full characterization of the adsorption behavior of the mixture and the columns is no longer required. In this ‘cycle to cycle’ control scheme, the measurements, optimization and control actions are performed once in every cycle. This paper presents simulation results of the control scheme applied to the separation of binary mixtures characterized by generalized Langmuir isotherms. The results are presented and analyzed in the frame of the triangle theory that has been recently extended to encompass these types of isotherms. Besides, online optimum performance of the SMB unit is compared with off-line optimization carried out using genetic algorithm. The results show that the controller fulfills the product and process specifications while operating the SMB unit optimally, regardless of the different types of Langmuir isotherms that the systems exhibit.