Advantage of Low‐Cost Predictive Control: Study Case on a Train of Distillation Columns |
| |
| Authors: | Cristina I Muresan Clara M Ionescu Eva H Dulf Roxana Rusu-Both Silviu Folea |
| |
| Affiliation: | 1. Technical University of Cluj-Napoca, Department of Automation, Cluj-Napoca, Romania;2. Ghent University, DYSC research group, Ghent, Belgium;3. Ghent University, Flanders Make, EEDT group, Ghent, Belgium |
| |
| Abstract: | The process of enriching the 13C isotope, performed in trains of cryogenic distillation columns, exhibits large settling times, nonlinearities, large dead‐times, and are difficult to model precisely. Such equipment has been developed in Romania, with concentration increasing up to 70 %. A control analysis for a single unit has already been done including a decentralized multivariable PI controller and two decoupling control algorithms based on the internal model control (IMC) approach. Here, a multivariable predictive controller, the extended prediction self‐adaptive controller is proposed. The simulation results, considering significant modeling errors, demonstrate that this represents a more suitable choice than the previously designed strategies. Comparisons are included to support this idea. |
| |
| Keywords: | Closed‐loop performance Cryogenic distillation columns EPSAC controller Isotope separation |
|
|
