Integrating data-based modeling and nonlinear control tools for batch process control

This work presents a data-based multi-model approach for modeling batch systems in which multiple local linear models are identified using partial least squares (PLS) regression and then combined with an appropriate weighting function that arises from fuzzy c-means clustering. The resulting data-based model is used to generate estimates of empirical reverse-time reachability regions (RTRRs) (defined as the set of states from where the …