The aim of this work is to compare several of the commercial dynamic models for batch distillation available worldwide. In this context, BATCHFRAC™, CHEMCAD™ BATCH, and HYSYS.Plant® software performances are compared to experimental data. The software can be used as soft sensors, playing the roll of ad-hoc observers or estimators for control objectives. Rigorous models were used as an alternative to predict the concentration profile and to specify the optimal switching time from products to slop cuts. The performance of a nonlinear model obtained using a novel identification algorithm was also studied. In addition, the strategy for continuous separation was revised with residue curve map analysis using Aspen SPLIT™.
batch distillation; residue curve map; soft sensor; inferential control; nonlinear identification
