Composition Control and Kalman Filtering in Emulsion Copolymerization

Abstract

Composition control of the sub-micron latex particles in the semicontinuous emulsion copolymerization of vinyl acetate / n-butyl acrylate is investigated. A stochastic approach is employed to compensate for modeling inaccuracies and measurement errors and an adaptive Kalman filter is used to estimate simultaneously the process states and the statistics of the noise vectors. A combined feedforward/feedback controller is derived to maintain constant copolymer composition in the latex particles. The controller operates on the Kalman filter estimates and manipulates the monomer addition rates to the polymer reactor.