Project number:
VEGA 1/0297/22
Title of the project:
Controller design methods for low-level carbon footprint process automation
Grant scheme:
VEGA
Project type:
VEGA Research Projects
Project duration (start):
01.01.2022
Project duration (end):
31.12.2025
Principal investigator:
Juraj Oravec
Deputy investigator:
Radoslav Paulen
Investigators:
Peter Bakaráč, Ľuboš Čirka, Diana Dzurková, Rastislav Fáber, Kristína Fedorová, Miroslav Fikar, Lenka Galčíková, Juraj Holaza, Michaela Horváthová, Martin Kalúz, Martin Klaučo, Roman Kohút, Alajos Mészáros, Martin Mojto, Erika Pavlovičová, Richard Valo, Jozef Vargan, Anna Vasičkaninová

The project aims to develop advanced controller design methods for low-level carbon footprint process automation. Decreased energy consumption is achieved by implementing the advanced methods of model predictive control. These methods are based on the robust control approach, parallel computing, machine learning, and economic criteria. The model predictive control methods will be designed considering the requirements of the chemical, biochemical, pharmaceutical, and food industries. However, the implementation range will not be limited just to these fields of industry. The theoretical results of the project will be implemented and experimentally analyzed using laboratory devices. The practical aspects of implementation on standard industrial hardware will be considered to design the advanced control methods for low-level carbon footprint process automation.

Publications

2023

  1. R. Dyrska – M. HorváthováP. Bakaráč – M. Mönnigmann – J. Oravec: Heat exchanger control using model predictive control with constraint removal. Applied Thermal Engineering, vol. 227, 2023.   Zenodo
  2. R. Fáber – K. Ľubušký – M. Mojto – R. Paulen: Enhancing Industrial Data Analysis through Machine Learning-based Classification of Petrochemical Datasets. In 49th International Conference of the Slovak Society of Chemical Engineering SSCHE 2023, Slovak Society of Chemical Engineering, Bratislava, SK, pp. 160–160, 2023.   Zenodo
  3. R. Fáber – K. Ľubušký – R. Paulen: Machine Learning-based Classification of Online Industrial Datasets. Editor(s): R. Paulen and M. Fikar, In Proceedings of the 2023 24th International Conference on Process Control, IEEE, Slovak University of Technology in Bratislava, Radlinského 9, 81237, Bratislava, Slovakia, pp. 132–137, 2023.   Zenodo
  4. K. Fedorová – Y. Jiang – J. Oravec – C. Jones – M. Kvasnica: A Generalized Stopping Criterion for Real-Time MPC with Guaranteed Stability. In 62nd IEEE Conference on Decision and Control, IEEE, Singapore, pp. 4705–4710, 2023.   Zenodo
  5. L. Galčíková – P. Belková – J. Oravec: Real-time tuning of approximated explicit MPC of a heat exchanger. Editor(s): R. Paulen and M. Fikar, In Proceedings of the 24th International Conference on Process Control - Summaries Volume, Slovak Chemical Library, Slovak University of Technology in Bratislava, Radlinského 9, SK812-37, Bratislava, Slovakia, pp. 38–38, 2023.   Zenodo
  6. J. HolazaL. GalčíkováJ. OravecM. Kvasnica: A software package for MPC design and tuning: MPT+. In 62nd IEEE Conference on Decision and Control, IEEE, Singapore, pp. 5682–5689, 2023.
  7. J. Holaza – K. Kvasnicová – E. PavlovičováJ. Oravec: Tube MPC Extension of MPT: Experimental Analysis. Editor(s): R. Paulen and M. Fikar, In Proceedings of the 2023 24th International Conference on Process Control, IEEE, Slovak University of Technology in Bratislava, Radlinského 9, 81237, Bratislava, Slovakia, pp. 120–125, 2023.   Zenodo
  8. M. HorváthováL. GalčíkováM. KlaučoJ. Oravec: Real-Time Optimisation-Based Robust Control: Heat Exchanger Comparative Analysis. In 62nd IEEE Conference on Decision and Control, IEEE, Singapore, pp. 6535–6540, 2023.
  9. M. HorváthováJ. Oravec: Approximated Convex-lifting-based Robust Control for a Heat Exchanger. Editor(s): R. Paulen and M. Fikar, In Proceedings of the 24th International Conference on Process Control - Summaries Volume, Slovak Chemical Library, Slovak University of Technology in Bratislava, Radlinského 9, SK812-37, Bratislava, Slovakia, 2023.   Zenodo
  10. R. KohútE. PavlovičováK. FedorováJ. OravecM. Kvasnica: Real-Time Deep-Learning-Driven Parallel MPC. In 62nd IEEE Conference on Decision and Control, IEEE, Singapore, 2023.   Zenodo
  11. M. Mojto – K. Ľubušký – M. FikarR. Paulen: Comparing Linear and Nonlinear Soft Sensor Approaches for Industrial Distillation Columns (in Anglo-Saxon). In 49th International Conference of the Slovak Society of Chemical Engineering SSCHE 2023, Slovak Society of Chemical Engineering, Bratislava, SK, pp. 159–159, 2023.   Zenodo
  12. M. Mojto – K. Ľubušký – M. FikarR. Paulen: Input Structure Selection for Soft-Sensor Design: Does It Pay Off?. Editor(s): R. Paulen and M. Fikar, In Proceedings of the 2023 24th International Conference on Process Control, IEEE, Slovak University of Technology in Bratislava, Radlinského 9, 81237, Bratislava, Slovakia, pp. 162–167, 2023.   Zenodo
  13. M. Mojto – K. Ľubušký – M. FikarR. Paulen: Data-Driven Indication of Flooding in an Industrial Debutanizer Column. Editor(s): Antonis Kokossis, Michael C. Georgiadis, Efstratios N. Pistikopoulos, In 33rd European Symposium on Computer Aided Process Engineering, Elsevier, no. 1, vol. 33, pp. 1001–1006, 2023.   Zenodo
  14. M. Mojto – K. Ľubušký – M. FikarR. Paulen: Design of Multi-Model Linear Inferential Sensors with SVM-based Switching Logic. In IFAC World Congress 2023, Yokohama, Japan, pp. 2545–2550, 2023.     Zenodo
  15. M. Mojto – K. Ľubušký – M. FikarR. Paulen: Data-Based Design of Multi-Model Inferential Sensors. Computers & Chemical Engineering, vol. 178, 2023.   arXiv   Zenodo
  16. J. Oravec: Distributed Version Control System Git (in Slovak), Vydavateľstvo FCHPT, 2023.
  17. J. OravecP. BakaráčE. PavlovičováM. Fikar: Smart Eco Greenhouse VESNA. In IFAC World Congress 2023, Yokohama, Japan, pp. 10295–10300, 2023.   Zenodo
  18. E. PavlovičováJ. Oravec: Distributed Model Predictive Control Design for a Laboratory Device. Editor(s): R. Paulen and M. Fikar, In Proceedings of the 24th International Conference on Process Control - Summaries Volume, Slovak Chemical Library, Slovak University of Technology in Bratislava, Radlinského 9, SK812-37, Bratislava, Slovakia, pp. 50–50, 2023.   Zenodo
  19. M. Ružička – I. Helgeland – R. Paulen: Modelling of a Forward Osmosis Process (in Slovak). In Membránové procesy pro udržitelný rozvoj - MEMPUR 2023, pp. 35–36, 2023.
  20. J. Vargan – J. Puk – K. Ľubušký – M. Fikar: Steady-State Analysis of Industrial MPC Controllers. Editor(s): R. Paulen and M. Fikar, In Proceedings of the 24th International Conference on Process Control - Summaries Volume, Slovak Chemical Library, Slovak University of Technology in Bratislava, Radlinského 9, SK812-37, Bratislava, Slovakia, 2023.   Zenodo

2022

  1. P. BakaráčM. HorváthováL. GalčíkováJ. Oravec – M. Bakošová: Approximated MPC for embedded hardware: Recursive random shooting approach. Computers & Chemical Engineering, vol. 165, 2022.
  2. R. Fáber – R. Valo – M. Roman – R. Paulen: Towards Temperature Monitoring in Long-Term Grain Storage. In 2022 Cybernetics & Informatics (K&I), pp. 1–6, 2022.   Zenodo
  3. M. FikarM. KlaučoR. Paulen: Theory of Automatic Control I. Practice Examples, FCHPT STU v Bratislave, 2022.
  4. L. GalčíkováM. HorváthováJ. Oravec – M. Bakošová: Self-Tunable Approximated Explicit Model Predictive Control of a Heat Exchanger. Chemical Engineering Transactions, 2022, Vol. 94, no. 94, pp. 1015–1020, 2022.
  5. A. R. Gottu Mukkula – R. Paulen: Robust Design of Optimal Experiments Considering Consecutive Re-Designs. Editor(s): Luis Ricardez-Sandoval, Jesus Pico, In 13th IFAC Symposium on Dynamics and Control of Process Systems, including Biosystems, IFAC, pp. 14–19, 2022.
  6. M. HorváthováL. GalčíkováJ. Oravec: Control Design for a Nonlinear Reactors-Separator Plant. In 2022 Cybernetics & Informatics (K&I), pp. 1–6, 2022.
  7. J. MiklešĽ. ČirkaJ. OravecM. Fikar: Design of H2 and Hinf control using Lyapunov functions (in Slovak), FCHPT STU v Bratislave, 2022.
  8. M. Mojto – K. Ľubušký – M. FikarR. Paulen: Data-based Design of Inferential Sensors for an Industrial Depropanizer Column with Data Pre-treatment Analysis. Editor(s): Mário Mihaľ, In 48th International Conference of the Slovak Society of Chemical Engineering SSCHE 2022 and Membrane Conference PERMEA 2022, Slovak Society of Chemical Engineering, Bratislava, SK, pp. 200, 2022.
  9. M. Mojto – K. Ľubušký – M. FikarR. Paulen: Support Vector Machine-based Design of Multi-model Inferential Sensors. Editor(s): Ludovic Montastruc, Stephane Negny, In 32nd European Symposium on Computer Aided Process Engineering, Elsevier, no. 1, vol. 32, pp. 1045–1050, 2022.
  10. M. Mojto – K. Ľubušký – M. FikarR. Paulen: Multi-Model Soft-Sensor Design for a Depropanizer Distillation Column. In Advanced Process Modelling Forum 18-19 October 2022, 2022.   Zenodo
  11. J. OravecM. Klaučo: Real-time tunable approximated explicit MPC. Automatica, vol. 142, pp. 110315, 2022.
  12. J. Shi – Y. Jiang – J. Oravec – B. Houska: Parallel MPC for Linear Systems with State and Input Constraints. IEEE Control Systems Letters, vol. 7, pp. 229–234, 2022.

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