Shaping of Molecular Weight Distribution Using Self-Optimizing Control Based on Moments

Abstract

It is important but also challenging to control the full shape of the molecular weight distribution in polymerization processes, since it is an infinite dimensional probability density function (PDF). In this work, a self-optimizing control (SOC) strategy is adopted to achieve the aim of PDF shaping by maintaining some elaborately selected controlled variables (CVs) at constant set points through online feedback control, even in the presence of uncertainties. To find optimal CVs, finite moments rather than the full shape, which corresponds to an infinite-dimensional space, of the PDF are adopted as elements to parametrize CVs, while the optimization problem is to minimize the distance between the actual PDF and the target PDF. The proposed SOC-PDF method is demonstrated more effective than the existing stochastic distribution control method through a pilot semibatch styrene polymerization case study.