Model Predictive Control for Batch Processes Using Latent Variable Methods

A novel multivariate model predictive control strategy for trajectory tracking and disturbance rejection for batch processes, based on multi way PCA models, is presented. It directly computes the manipulated variable trajectory adjustments over a future horizon using the structure of the PCA model. The advantages and the modest data requirements are illustrated using an emulsion polymerization process for temperature tracking.