Polynomial ARMA model identification for a continuous styrene polymerization reactor using on-line measurements of polymer properties

Abstract

The multiinput–multioutput identification for a continuous styrene polymerization reactor using a polynomial ARMA model is carried out by both simulation and experiment. The pseudorandom multilevel input signals are applied for model identification in which input variables are the jacket inlet temperature and the feed flow rate, whereas the output variables are the monomer conversion and the weight-average molecular weight. The use of a polynomial ARMA model for identification of the multivariable polymerization reaction system is validated by simulation study. For the experimental corroboration, correlations are developed to convert the on-line measurements of density and viscosity of the reaction mixture to the monomer conversion and the weight-average molecular weight. The on-line values of the conversion and weight-average molecular weight turn out to be in good agreement with the off-line measurements. Despite the complex and nonlinear features of the polymerization reaction system, the polynomial ARMA model is found to satisfactorily describe the dynamic behavior of the polymerization reactor. Therefore, one may apply the polynomial ARMA model to the optimization and control of polymerization reactor systems. © 2000 John Wiley & Sons, Inc. J Appl Polym Sci 76: 1889–1901, 2000