Reduced-order model for monitoring spectroscopic and chromatographic polymer properties
A reduced-order mechanistic polymerization model and its application in the design of a low-dimension multi-rate state estimator (soft sensor) for monitoring spectroscopic and chromatographic polymer properties are presented. A model reduction approach is used to simplify a method-of-moments mechanistic model. Using this approach, the order (number of the state variables) of the model is reduced from 20 to 7. The soft sensor estimates spectroscopic and chromatographic polymer properties from (a) frequent measurements of the reactor temperature and the flow rates of monomer (n-butyl acrylate), initiator (t-butyl peroxy acetate) solution and solvent (xylene) feed streams, and (b) infrequent and delayed measurements of polymer number- and weight-average molecular weights and the concentrations of terminal solvent groups, terminal double bonds and short chain branches. The benefits of using the infrequent measurements in the estimation are shown. The soft sensor is implemented in real-time, and the calculated continuous estimates of polymer number- and weight-average molecular weights and the concentrations of solvent, terminal double bonds and short chain branches are compared to the corresponding chromatographic and spectroscopic measurements. Copyright (C) 2007 John Wiley & Sons, Ltd.
state estimation model reduction spectroscopic measurements free-radical solution polymerization mathematical modeling microstructure properties process monitoring chromatographic measurements