NONLINEAR STATE ESTIMATION TECHNIQUES APPLIED TO POLYMER PROCESSES

GALDEANO, RUBÉN; ASTEASUAIN, MARIANO; SÁNCHEZ, MABEL

Los Cocos, Córdoba, Argentina

Simposio; V Argentine-Chilean Polymer Symposium (ARCHIPOL'09); 2009

PLAPIQUI, INTEMA, INTEC, UNS, UNMDP, UNL, UNC

The control and on line optimization of polymer properties in a continuous process is an extremely important and yet largely unsolved problem. In order to improve the overall process performance, Dynamic Real Time Optimization (DRTO) closed loops have begun to implemented. DRTO loops comprise stateestimation, dynamic optimization and control tasks. The Extended Kalman Filter is probably the most commonly used estimator. However, under certain situations this technique may present problems, particularly for high nonlinear systems such as polymer processes. In this work, to new non linear filtering methods which intend to overcome the disadvantages of the Extended Kalman Filter, the Recursive Nonlinear Dynamic Data Reconciliation and the Particle Filter, are analyzed when applied to a polymer process