Repetitive control and optimization of SMB process
نویسندگان
چکیده
A two-tier optimizing control strategy of a simulated moving bed (SMB) process has been studied on the basis of repetitive control. Repetitive model predictive control (RMPC) of product purities is carried out in the lower tier and the optimum feed and desorbent flow rates and the length of switching period are determined in the upper tier. Both of them are based on a fundamental SMB model which is reduced to a set of nonlinear discrete-time dynamic equations using the cubic spline collocation method and exact discretization. For RMPC, the SMB model is linearized successively around the operating trajectories in the previous switching period for every step. Numerical studies with linear isotherms showed that the proposed strategy satisfactorily attains the intended optimum while robustly regulating the product purities against various uncertainties.
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