Dynamic Optimization of a Simulated Moving Bed (SMB) Chromatographic Separation Process

2006 ◽  
Vol 45 (26) ◽  
pp. 9033-9041 ◽  
Author(s):  
María-Sonia G. García ◽  
Eva Balsa-Canto ◽  
Julio R. Banga ◽  
Alain Vande Wouwer
Keyword(s):  
Dynamic Optimization ◽  
Chromatographic Separation ◽  
Separation Process ◽  
Simulated Moving Bed ◽  
Moving Bed

Digitized Simulation of the Moving Bed

2020 ◽  
Vol 987 ◽  
pp. 157-161
Author(s):  
Chao Fan Xie ◽  
Rey Chue Huang ◽  
Lin Xu ◽  
Fu Quan Zhang ◽  
Lu Xiong Xu
Keyword(s):  
Stationary Phase ◽  
Chromatographic Separation ◽  
Manufacturing Process ◽  
Theoretical Basis ◽  
Mobile Phase ◽  
Separation Process ◽  
Simulated Moving Bed ◽  
Moving Bed ◽  
Simulated Moving Bed Chromatography ◽  
Chemical Products

Chromatographic separation is an indispensable and important technology in the manufacturing process of chemical products and biomedicine. It uses the distribution differences of a compound in the stationary phase and mobile phase to achieve the separation of the mixture. It is of great value to study the separation process of substances by simulated moving bed chromatography. By digitally simulating the process of moving bed, we can observe the influence of parameter changes on substance analysis by chromatography, and then find out the law of substance separation, which can provide theoretical basis for scientific research of biopharmaceuticals.

scholarly journals Model Predictive Control Method of Simulated Moving Bed Chromatographic Separation Process Based on Subspace System Identification

2019 ◽  
Vol 2019 ◽  
pp. 1-24 ◽  
Author(s):  
Zhen Yan ◽  
Jie-Sheng Wang ◽  
Shao-Yan Wang ◽  
Shou-Jiang Li ◽  
Dan Wang ◽  
...  
Keyword(s):  
System Identification ◽  
State Space ◽  
Predictive Control ◽  
Chromatographic Separation ◽  
Control Method ◽  
Separation Process ◽  
Simulated Moving Bed ◽  
Moving Bed ◽  
Separation Technology ◽  
Subspace System Identification

Simulated moving bed (SMB) chromatographic separation is a new type of separation technology based on traditional fixed bed adsorption operation and true moving bed (TMB) chromatographic separation technology, which includes inlet-outlet liquid, liquid circulation, and feed liquid separation. The input-output data matrices were constructed based on SMB chromatographic separation process data. The SMB chromatographic separation process was modeled by utilizing two subspace system identification algorithms: multivariable output-error state-space (MOESP) identification algorithm and numerical algorithms for subspace state-space system identification (N4SID), so as to obtain the 3rd-order and 4th-order state-space yield models of the SMB chromatographic separation process, respectively. The model predictive control method based on the established state-space models is used in the SMB chromatographic separation process. The influence of different control indicators on the predictive control system response performance is discussed. The output response curves of the yield models were obtained by changing the related parameters so that the yield model parameters are optimized set meanwhile. Finally, the simulation results showed that the yield models are successfully controlled based on the each control period and given yield range.

OPTIMAL CONTROL of the SIMULATED MOVING BED (SMB) CHROMATOGRAPHIC SEPARATION PROCESS

2007 ◽  
Vol 40 (5) ◽  
pp. 183-188 ◽  
Author(s):  
María-Sonia G. García ◽  
Eva Balsa-Canto ◽  
Alain Vande Wouwer ◽  
Julio R. Banga
Keyword(s):  
Optimal Control ◽  
Chromatographic Separation ◽  
Separation Process ◽  
Simulated Moving Bed ◽  
Moving Bed
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