Model Predictive Control of Simulated Moving Bed Chromatography for Binary and Pseudo-binary Separations: Simulation Study

Abstract Simulated moving bed (SMB) processes have been applied to petrochemical, pharmaceutical, and fine chemical industries to separate products in high purity and yield since it was introduced in 1960s. Owing to process complexity and operational sensitivity, the control and dynamic optimization of the SMB process are still challenging issues. In this work, a simplified process model with linear isotherms was introduced to estimate process states of conventional four-zone SMB chromatography. In a simulation study, a controller can estimate current process states and find the optimal operating conditions ‘switch by switch’ up to moderately nonlinear ranges of the competitive Langmuir isotherms. Furthermore, the controller works for the process with system void volumes and delayed feedback information.

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