摘要：AbstractIn this work, we propose a control-relevant multiple linear modeling approach for simulated moving bed chromatography (SMBC) by linearizing the first principles model at carefully chosen equilibrium points. Subsequently, sub-models to account for port switching for each of the linear model are obtained. Model aggregation is done using Bayesian weighting to generate multiple model predictions for the nonlinear dynamics of SMBC. The multiple model approach is validated using simulations for cyclic steady state (CSS) of SMB as well as for a transition between two optimal CSS points for separation of a glucose- fructose mixture.
关键词：KeywordsSimulated moving bed chromatographyseparation processcyclic steady stateglucose-fructose systemmultiple linear modelingBayesian approach
