Artículos de revistas
Unscented Kalman Filter. Application of the robust approach to polymerization processes
Fecha
2017-10Registro en:
Tupaz Pantoja, Jhovany Alexander; Asteasuain, Mariano; Sanchez, Mabel Cristina; Unscented Kalman Filter. Application of the robust approach to polymerization processes; Elsevier; Computer Aided Chemical Engineering; 40; 10-2017; 1477-1482
1570-7946
CONICET Digital
CONICET
Autor
Tupaz Pantoja, Jhovany Alexander
Asteasuain, Mariano
Sanchez, Mabel Cristina
Resumen
The control of polymerization processes has central importance because operational conditions affect the processing and end-use properties of the product. The nonlinear controllers based upon rigorous models make use of the on-line state estimates obtained from the available measurements. For polymerization processes, the Unscented Kalman Filter has shown a rewarding performance for state estimation. Because the presence of outliers distorts the behaviour of the filter, Robust Statistics-based approaches have been proposed to reduce their detrimental effect on variable estimates. Until now, only Huber type M-estimators have been used as loss function of the estimation problem. In this work, the ability of other types of M-estimators to improve estimate robustness without introducing numerical problems is analysed. The performances of the M-estimators are compared for a copolymerization process within the framework of a filtering technique based on the Unscented Transformation, which uses a reformulation of the covariance of measurements errors.