GEOMETRIC ESTIMATION OF TERNARY DISTILLATION COLUMNS

The problem of estimating effluent compositions from temperature measurements in ternary distillation columns is addressed within a geometric estimation framework where the estimation structure and the algorithm are jointly designed. The employment of passive estimation structures and error propagation measures yields criteria to choose the sensor number and locations as well as the set of innovated states. The proposed approach is tested with experimental data from a 32-stage pilot column (tert-butanol-ethanol-water system). With 64 on-line dynamical equations and a straightforward tuning scheme, the proposed estimator yields the same behaviour than the one of an Extended Kalman Filter with 2144 equations and an optimization-based tuning procedure