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State estimation for continuous emulsion polymerization
Author(s) -
Gag Louise,
Macgregor J. F.
Publication year - 1991
Publication title -
the canadian journal of chemical engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.404
H-Index - 67
eISSN - 1939-019X
pISSN - 0008-4034
DOI - 10.1002/cjce.5450690307
Subject(s) - emulsion polymerization , robustness (evolution) , kalman filter , control theory (sociology) , polymerization , estimator , emulsion , computer science , mathematics , materials science , engineering , chemical engineering , chemistry , control (management) , polymer , statistics , biochemistry , artificial intelligence , composite material , gene
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.