State estimation for continuous emulsion polymerization

Abstract

Abstract Various aspects of the use of extended Kalman Filters for tracking the states of continuous emulsion polymerization reactors are investigated. The importance of introducing meaningful nonstationary stochastic states to account for unknown impurities, initiator efficiencies, modelling errors, etc. is illustrated. The robustness of these state estimators to unmodelled and unmeasured disturbances, to modelling errors, and to input errors is evaluated. A procedure for selecting an optimal set of on‐line sensors is presented. The emulsion polymerization of styrene‐butadiene rubber (SBR) is used as the example system.