Parameter estimation and iterative set-point optimization of Continuous Annular Electrochromatography

Abstract

Continuous Annular Electro-Chromatography (CAEC) is a novel high performance continuous separation process for high value substances. It results from the combination of the two techniques of (capillary) electro-chromatography and annular chromatography. We describe an iterative online optimization scheme for this process based upon chromatograms measured at one fixed location at the outlet. A parameter identification step is incorporated into the iterative optimization to reduce the plant/model mismatch. Selected model parameters are updated by identifying a 1D batch column model from the measured data and the parameters are used in a 2D model of the annular process. The optimization is based upon the 2D model of the apparatus and the gradient modification technique that has been proposed for the optimization of batch chromatography by Gao and Engell [1].