Model identification for control of a distillation column

This paper presents the system identification techniques as an alternative to model processes for control purposes. A methodology for obtaining adequate empirical models for distillation columns is presented. This methodology is applied to a benchmark of a distillation column at laboratory scale (Column A). In this work, experimental data fit a state space model using subspace identification techniques.