Optimization of the Parameters of a Model Predictive Control System for an Industrial Fractionator
-
Published:2024-07
Issue:7
Volume:85
Page:738-745
-
ISSN:0005-1179
-
Container-title:Automation and Remote Control
-
language:
-
Short-container-title:ARC
Author:
,Snegirev O. Yu.,Torgashov A. Yu.,
Abstract
The problem of parametric synthesis of a model predictive control (MPC) system by the chemical process of production of the kerosene fraction of an industrial fractionator under conditions of constraints and uncertainty is considered. The optimal parameters of the MPC algorithm are obtained as a result of solving the problem of multi-criteria optimization, taking into account the intervally specified parameters of the plant model.
Publisher
The Russian Academy of Sciences
Reference10 articles.
1. 1. Qian, X., Jia, S., Huang, K., Chen, H., Yuan, Y., and Zhang, L., Model predictive control of azeotropic dividing wall distillation column for separating furfural-water mixture, Optimality and Robustness, ISA transactions, 2021, vol. 111, pp. 302-308. 2. 2. Martin, P.A., Zanin, A.C., and Odloak, D., Integrating real time optimization and model predictive control of a crude distillation unit, Brazilian Journal of Chemical Engineering, 2019, vol. 36, pp. 1205-1222. 3. 3. Mendis, P., Wickramasinghe, C., Narayana, M., and Bayer, C., Adaptive model predictive control with successive linearization for distillate composition control in batch distillation, 2019 Moratuwa Engineering Research Conference, 2019, pp. 366-369. 4. 4. Schwenzer, M., Ay, M., Bergs, T., and Abel, D., Review on model predictive control: an engineering perspective, The International Journal of Advanced Manufacturing Technology, 2021, vol. 117, pp. 1327-1349. 5. 5. Seborg, D.E., Edgar, T.E., Mellichamp, D.A., and Doyle, III F.J., Process Dynamics and Control, 4nd ed., John Wiley & Sons, 2016, pp. 369-389.
|
|