Repetitive Control and Cyclic Steady State Optimization of a Simulated Moving Bed Process*

A two-tier optimizing control strategy for the simulated moving bed (SMB) process proposed in Kim et al.Kim (2010) has been studied experimentally as well as numerically. The strategy was designed to carry out repetitive model predictive control (RMPC) of average product purities in the lower tier and off-line cyclic steady state optimization of feed and desorbent flow rates and the length of switching period in the upper tier. Experimental studies have been conducted in a four zone SMB system to separate L-ribose and L-arabinose from their mixture dissolved in water for the linear isotherm case and numerical studies have been carried out for the nonlinear isotherm case. As a consequence, the optimizing control strategy is observed to satisfactorily attain the intended optimum while robustly regulating the product purities against various uncertainties.