Feedback regulation in preparative elution chromatography

Input-output models utilizing discrete variables are developed for elution chromatography and used together with control theory to investigate behavior patterns between output variables (e.g., yield, purity, and production rate) and input variables (e.g., cut point locations and feed slug size). Variable interactions and controllability characteristics for isocratic and stepwise gradient elution in linear and nonlinear chromatography are investigated by using the relative gain array, singular value decomposition, and direct simulation. Inverse-based regulatory systems are evaluated for updating process inputs by using information on process outputs such that product quality and system performance parameters are efficiently maintained for the case where the column is overloaded and the solute peaks overlap with each other. Strategies for feedback optimizing control are also discussed.