Research on Optimization of Simulated Moving Bed Separation Process

Chromatographic processes provide an effective method for the separation of multicomponent mixtures in which the components have different adsorption affinities. As an alternative to conventional discontinuous batch chromatography process, the simulated moving bed (SMB) chromatographic separation process is a continuous process and has gained more and more application in such fields as petrochemicals, pharmaceutical, and food industries recently. However, optimization of SMB processes is still a challenging task, particularly when a rigorous first-principles process model is used. SMB processes exhibit strong nonlinear behavior and they are of periodic nature. Additionally, their hybrid, non-steady and non-ideal characteristics have to be taken into account. Model-based optimization strategies are therefore of great importance for research and practice. In this paper, the dynamic optimization problem arising from SMB processes is presented, and the simulation results show its effectiveness and usability.