Batch-to-batch optimization of PSD in emulsion polymerization using a hybrid model

This work presents a hybrid modeling approach for batch-to-batch optimization of particle size distributions (PSD) in semi-batch emulsion polymerization. A fundamental population balance model describing PSD evolution is augmented by a Partial Least Squares (PLS) model. This hybrid model is then embedded in a successive quadratic program (SQP) to design surfactant and initiator input trajectories that drive the process to a target PSD. PLS using a moving batch data history, in which earlier batches are dropped from the data set as more recent batches are added, leads to superior convergence compared with an expanding data set.