Optimizing control of simulated moving beds--experimental implementation.

The operation of simulated moving beds (SMBs) at their optimal operating conditions is difficult and not robust. Therefore, it is common practice to operate SMB units far from their economic optimum in order to tolerate uncertainties in the system and minimize the effect of disturbances. Recently, we have proposed an on-line optimization based SMB control scheme that allows to exploit the full economic potential of SMB technology. The goal of this work is two-fold. Firstly, to experimentally evaluate and demonstrate the capability of the controller to optimize and operate the SMB units, thus delivering the products with maximum productivity and minimum solvent consumption. Secondly, to show the suitability of the controller even using a minimum of system information, thus making the detailed isotherm measurements redundant and saving time in the separation design phase. This paper reports and discusses the first experimental implementation of the control concept on a high purity separation of nucleosides (uridine, guanosine) with an eight-column four-section SMB where the species to be separated are retained on the source 30RPC stationary phase according to a linear isotherm.

[1]  Manfred Morari,et al.  Optimizing control of simulated moving beds--linear isotherm. , 2004, Journal of chromatography. A.

[2]  Massimo Morbidelli,et al.  Design of Simulated Moving Bed Units under Nonideal Conditions , 1999 .

[3]  Massimo Morbidelli,et al.  Optimal operation of simulated moving bed units for nonlinear chromatographic separations , 1997 .

[4]  Jay H. Lee,et al.  Automatic control of simulated moving beds , 2004 .

[5]  Achim Kienle,et al.  Simulated moving bed process with cyclic modulation of the feed concentration. , 2003, Journal of chromatography. A.

[6]  Massimo Morbidelli,et al.  Simulated moving‐bed units with extra‐column dead volume , 1999 .

[7]  Manfred Morari,et al.  Online optimization based feedback control of simulated moving bed chromatographic units , 2004 .

[8]  Manfred Morari,et al.  Optimization based adaptive control of Simulated Moving Beds , 2003 .

[9]  Manfred Morari,et al.  Optimizing control of an experimental simulated moving bed unit , 2006 .

[10]  Sebastian Engell,et al.  Model-based optimization and control of chromatographic processes , 2000 .

[11]  Achim Kienle,et al.  Optimal operation of simulated moving bed chromatographic processes by means of simple feedback control. , 2003, Journal of chromatography. A.

[12]  Jay H. Lee,et al.  A model-based predictive control approach to repetitive control of continuous processes with periodic operations , 2001 .

[13]  Manfred Morari,et al.  Automatic Control of Simulated Moving Beds—Experimental Verification , 2005 .

[14]  G. Subramanian,et al.  Bioseparation and Bioprocessing , 1998 .

[15]  Manfred Morari,et al.  Automatic Control of Simulated Moving Beds II: Nonlinear Isotherm , 2004 .

[16]  Jay H. Lee,et al.  Repetitive model predictive control applied to a simulated moving bed chromatography system , 2000 .

[17]  Ernst Dieter Gilles,et al.  Automatic control of the simulated moving bed process for C8 aromatics separation using asymptotically exact input/output-linearization , 1999 .

[18]  Chaoyong Wang,et al.  Neural network-based identification of SMB chromatographic processes , 2001 .

[19]  Karsten-Ulrich Klatt,et al.  Model-based control of a simulated moving bed chromatographic process for the separation of fructose and glucose , 2002 .

[20]  Olivier Ludemann-Hombourger,et al.  The “VARICOL” Process: A New Multicolumn Continuous Chromatographic Process , 2000 .

[21]  Marco Mazzotti,et al.  Experimental assessment of powerfeed chromatography , 2004 .

[22]  M. Morbidelli,et al.  Simulated moving-bed chromatography and its application to chirotechnology. , 2000, Trends in biotechnology.