Robust State Estimation of Polymerization Processes

SANCHEZ MABEL; ASTEASUAIN MARIANO; TUPAZ PANTOJA JHOVANY

Cancún - Rivera Maya

Congreso; XV Simposio Latinoamericano de Polímeros. XIII Congreso Iberoamericano de Polímeros; 2016

Sociedad Polimérica de México

The Unscented Kalman Filter (UKF) is based on a mechanism that propagates the mean and covariance of a random variable through a nonlinear transformation. Because the presence of outliers distorts variable estimates, robust estimators are devised that produce reliable estimates, not only when data follow a given distribution exactly, but also when this happens only approximately due to the presence of outliers. The aim of this paper is to compare the performance of different M-estimators in the framework of the UKF when they are applied to a copolymerization process