Batch distillation is a widely used separation process in chemical engineering.Due to the comparatively small investment and flexibility in production

batch distillation has found various industrial applications in biopharmaceuticals

fine chemicals production and foods processing.To guarantee high product quality

modeling and advanced process control for batch distillation have received significant attention. As an unsteady state dynamic process with strong nonlinearity

however

it is still not easy for engineers to design a control system on the basis of a simple model to guarantee good control performance for batch distillation.In this paper

by using the batch distillation model in Aspen Batch Distillation（ABD)as prototype

the process data of tower residual liquid and distillate compositions under different reflux ratios were obtained firstly.Based on the process data

then

the distillate volume and concentration of the process were formulated by the steady-state spline interpolation models（SIM).To compensate the dynamic error caused by variation of reflux ratios

a simple dynamic model was identified and combined with the steady-state SIM

resulting in a simple dynamic SIM for batch distillation.The comparison of the responses of the proposed SIM and ABD model to the time-varying reflux ratio indicated the applicability and precision of the proposed SIM.By using the SIM as the prediction model

a model predictive control （MPC)algorithm was further proposed for the concentration control of batch distillation.Numerical simulations demonstrated the applicability and robustness of the proposed control scheme for batch distillation with different feed compositions.The proposed control scheme lays a solid foundation for the further studies on online optimization of batch distillation.