Project number:
APVV-15-0007
Title of the project:
Optimal Control for Process Industries
Project type:
APVV Research Projects
Project duration (start):
01.01.2016
Project duration (end):
31.10.2020
Principal investigator:
Miroslav Fikar
Investigators:
Peter Bakaráč, Monika Bakošová, Ľuboš Čirka, Ján Drgoňa, Matúš Furka, Juraj Holaza, Michaela Horváthová, Deepak Ingole, Filip Janeček, Martin Jelemenský, Martin Kalúz, Karol Kiš, Martin Klaučo, Michal Kvasnica, Alajos Mészáros, Ján Mikleš, Martin Mojto, Juraj Oravec, Daniela Pakšiová, Radoslav Paulen, Ayush Sharma, Juraj Števek, Carlos E. Valero, Petra Valiauga, Richard Valo, Anna Vasičkaninová

Abstract

The main aim of the project is design of effective and advances methods of process control and study of optimal process operation. We will aim our attention mainly to processes with heat and mass transfer. These processes are inherently complex, exhibit nonlinearities and hybrid behaviour that has consequences in control quality and performance. Optimal control will include dynamic optimisation in continuous and discrete domains as a tool for qualitative analysis at upper process control level. Repeated dynamic optimisation at the lower lever yields algorithms of predictive control. This will result in characterisation of optimal operation regimes and controllers optimising processes and large units composed from them. Also important will be software implementation of proposed solutions, available to a larger community in open source code as well as verification in laboratory conditions.

Objectives
The aim of the proposed project is to investigate and design new methods in the area of automation and control in process industries to increase profitability, stability, and competitiveness. We will focus on study of processes that are not operated in steady-state. Their control is example of optimal operation on multiple levels. We will study vertical integration between upper and lower levels, safety of communication between levels, reduction of complexity and increase of intelligence (smartness) of the basic process control level.

Goals for the first phase, 2016-2017: Analysis and proposal of solution

  • Analysis and design of mathematical models for description of processes of chemical technologies.
  • Analysis of optimality of operation for separation processes.
  • Possibilities of complexity reduction of MPC.
  • Development of interface of MPT for export of optimal controllers to embedded devices(PLC, FPGA).

Goals for the second phase, 2017-2019: Development of methods

  • Robust predictive control of processes using Lyapunov functions.
  • Complexity reduction in number of regions of explicit MPC.
  • Explicit MPC for systems with a larger number of states.
  • Development of methods for optimal control of separation processes.
  • Horizontal and vertical integration of processes and controllers.

Goals for the third phase, 2019-2020: Validation and applications of methods

  • Reduction of suboptimality of the optimal control at the lower level.
  • Implementation of new methods of optima control with reduces memory and computational complexity.
  • Development and addition of software tools for analysis, synthesis, and implementation of optimal control.
  • Development and verification of intelligent devices for heat transfer processes.
  • Applications of optimal control methods in process control.

Solvers
OIRP

Publications

2020

  1. M. FurkaK. KišM. HorváthováM. MojtoM. Bakošová: Identification and Control of a Cascade of Biochemical Reactors. In 2020 Cybernetics & Informatics (K&I), 2020.
  2. A. R. Gottu Mukkula – P. Valiauga – M. FikarR. Paulen – S. Engell: Experimental Real Time Optimization of a Continuous Membrane Separation Plant (in ). In Preprints of the 21st IFAC World Congress (Virtual), Berlin, Germany, July 12-17, 2020, vol. 21, pp. 11967–11974, 2020.
  3. J. Holaza – J. OravecM. Kvasnica – R. Dyrska – M. Mönnigmann – M. Fikar: Accelerating Explicit Model Predictive Control by Constraint Sorting. In Preprints of the 21st IFAC World Congress (Virtual), Berlin, Germany, July 12-17, 2020, vol. 21, pp. 11520–11525, 2020.
  4. M. HorváthováJ. OravecM. Bakošová: Efficient Convex-Lifting-Based Robust Control of a Chemical Reactor. Chemical Engineering Transactions, vol. 81, pp. 865–870, 2020.
  5. Y. Jiang – J. Oravec – B. Houska – M. Kvasnica: Parallel MPC for Linear Systems with Input Constraints. IEEE Transactions on Automatic Control, pp. 1–8, 2020.
  6. M. KalúzĽ. ČirkaM. Fikar: ELab: A Lightweight SCADA System for Control Engineering Research and Education. In Preprints of the 21st IFAC World Congress (Virtual), Berlin, Germany, July 12-17, 2020, vol. 21, pp. 17469–17474, 2020.
  7. K. KišM. KlaučoA. Mészáros: Neural Network Controllers in Chemical Technologies. In 2020 IEEE 15th International Conference of System of Systems Engineering, IEEE, pp. 397–402, 2020.
  8. K. Kusumo – L. Gomoescu – R. Paulen – S. García Muñoz – C. C. Pantelides – N. Shah – B. Chachuat: Bayesian Approach to Probabilistic Design Space Characterization: A Nested Sampling Strategy (in ). Industrial & Engineering Chemistry Research, no. 6, vol. 59, pp. 2396–2408, 2020.
  9. K. Kusumo – L. Gomoescu – R. Paulen – S. García Muñoz – C. C. Pantelides – N. Shah – B. Chachuat: Nested Sampling Strategy for Bayesian Design Space Characterization (in ). Editor(s): Sauro Pierucci, Flavio Manenti, Giulia Luisa Bozzano, Davide Manca, In 30th European Symposium on Computer Aided Process Engineering, Elsevier, vol. 30, pp. 1957–1962, 2020.
  10. Y. Lohr – M. KlaučoM. Fikar – M. Mönnigmann: Machine Learning Assisted Solutions of Mixed Integer MPC on Embedded Platforms (in ). In Preprints of the 21st IFAC World Congress (Virtual), Berlin, Germany, July 12-17, 2020, vol. 21, 2020.
  11. L. Lu – M. Kvasnica: Low-Complexity Stabilizing PWA Controllers for Linear Systems with Parametric Uncertainties. In Preprints of the 21st IFAC World Congress (Virtual), Berlin, Germany, July 12-17, 2020, vol. 21, pp. 7376–7381, 2020.
  12. M. Mojto – K. Ľubušký – M. FikarR. Paulen: Advanced Process Control of an Industrial Depropanizer Column using Data-based Inferential Sensors (in ). Editor(s): Sauro Pierucci, Flavio Manenti, Giulia Luisa Bozzano, Davide Manca, In 30th European Symposium on Computer Aided Process Engineering, Elsevier, vol. 30, pp. 1213–1218, 2020.
  13. J. OravecM. HorváthováM. Bakošová: Energy efficient convex-lifting-based robust control of a heat exchanger. Energy, no. 201, pp. 1–11, 2020.
  14. J. OravecM. HorváthováM. Bakošová: Multivariable Robust MPC Design for Neutralization Plant: Experimental Analysis. European Journal of Control, 2020.
  15. R. Paulen – L. Gomoescu – B. Chachuat: Nested Sampling Approach to Set-membership Estimation (in ). In Preprints of the 21st IFAC World Congress (Virtual), Berlin, Germany, July 12-17, 2020, vol. 21, pp. 7318–7323, 2020.
  16. S. Thangavel – R. Paulen – S. Engell: Adaptive multi-stage NMPC using sigma point principles (in ). In European Control Conference 2020, pp. 196–201, 2020.
  17. S. Thangavel – R. Paulen – S. Engell: Robust Multi-Stage Nonlinear Model Predictive Control Using Sigma Points. Processes, no. 7, vol. 8, pp. 0851, 2020.
  18. S. Thangavel – R. Paulen – S. Engell: Multi-stage NMPC using sigma point principles. In 6th Conference on Advances in Control and Optimization of Dynamical Systems ACODS 2020, Elsevier, vol. 53, pp. 386–391, 2020.
  19. S. Thangavel – R. Paulen – S. Engell: Dual multi-stage NMPC using sigma point principles (in ). In Preprints of the 21st IFAC World Congress (Virtual), Berlin, Germany, July 12-17, 2020, vol. 21, pp. 11394–11401, 2020.
  20. J. Theunissen – A. Sorniotti – P. Gruber – S. Fallah – M. Ricco – M. Kvasnica – M. Dhaens: Regionless Explicit Model Predictive Control of Active Suspension Systems With Preview. IEEE Transactions on Industrial Electronics, no. 6, vol. 67, pp. 4877–4888, 2020.
  21. C. E. Valero – M. Villanueva – B. Houska – R. Paulen: Set-Based State Estimation: A Polytopic Approach (in ). In Preprints of the 21st IFAC World Congress (Virtual), Berlin, Germany, July 12-17, 2020, vol. 21, pp. 11428–11433, 2020.

2019

  1. P. BakaráčM. KlaučoJ. Oravec: Electronic Sensoric Board (in Slovak). 2019.
  2. P. BakaráčM. Kvasnica: Approximate explicit robust model predictive control of a CSTR with fast reactions (in ). Chemical papers, no. 3, vol. 73, pp. 611–618, 2019.
  3. M. Bakošová – R. Trautenberger – J. Derco – J. Kavor – P. Valiauga – J. OravecA. Vasičkaninová: Modelling and Control of a Carrousel Type Biochemical Reactor. Editor(s): M. Fikar and M. Kvasnica, In Proceedings of the 22nd International Conference on Process Control, Slovak Chemical Library, Štrbské Pleso, Slovakia, 2019.
  4. Ľ. ČirkaM. Kalúz – D. Dzurková – R. Valo: Educational Device Flexy2 in the Teaching of Experimental Identication. Editor(s): M. Fikar and M. Kvasnica, In Proceedings of the 22nd International Conference on Process Control, Slovak Chemical Library, Štrbské Pleso, Slovakia, pp. 239–244, 2019.
  5. W. Daosud – P. Kittisupakorn – M. Fikar – S. Lucia – R. Paulen: Efficient robust nonlinear model predictive control via approximate multi-stage programming: A neural networks based approach. Editor(s): Anton A. Kiss, Edwin Zondervan, Richard Lakerveld, Leyla Özkan, In 29th European Symposium on Computer Aided Process Engineering, Elsevier, vol. 29, pp. 571–576, 2019.
  6. K. Fedorová – P. BakaráčM. Kvasnica: Comparison of Two Approaches to Agile Manoeuvres via MPC. Editor(s): M. Fikar and M. Kvasnica, In Proceedings of the 22nd International Conference on Process Control, Slovak Chemical Library, Štrbské Pleso, Slovakia, 2019.
  7. K. Fedorová – P. BakaráčM. Kvasnica: Agile Manoeuvres using Model Predictive Control. Acta Chimica Slovaca, no. 1, vol. 12, pp. 136–141, 2019.
  8. M. Fikar: Optimal Control of Membrane Processes. In Process Systems Engineering (PSE) Asia, Chulalongkorn Unviersity, Bangkok, Thajsko, pp. 6–6, 2019.
  9. M. FurkaM. Klaučo: Development and Implementation of Control Algorithms for Furuta Pendulum. Editor(s): M. Fikar and M. Kvasnica, In Proceedings of the 22nd International Conference on Process Control, Slovak Chemical Library, Štrbské Pleso, Slovakia, 2019.
  10. M. FurkaM. KlaučoM. Kvasnica: Stabilization of Furuta Pendulum using Nonlinear MPC. Research Papers Faculty of Materials Science and Technology in Trnava, no. 45, vol. 27, pp. 42–48, 2019.
  11. L. Galčíková – J. OravecM. Bakošová: Advanced Robust MPC Design for Plate Heat Exchanger. Editor(s): M. Fikar and M. Kvasnica, In Proceedings of the 22nd International Conference on Process Control, Slovak Chemical Library, Štrbské Pleso, Slovakia, 2019.
  12. A. R. Gottu Mukkula – R. Paulen: Optimal experiment design in nonlinear parameter estimation with exact confidence regions. Journal of Process Control, vol. 83, pp. 187–195, 2019.
  13. M. HorváthováJ. OravecM. BakošováM. Kvasnica: Robust Convex-lifting-based Control Using Approximated Feedback Control Law. Editor(s): M. Fikar and M. Kvasnica, In Proceedings of the 22nd International Conference on Process Control, Slovak Chemical Library, Štrbské Pleso, Slovakia, 2019.
  14. M. KalúzM. KlaučoĽ. ČirkaM. Fikar: Flexy2: A Portable Laboratory Device for Control Engineering Education. In 12th IFAC Symposium Advances in Control Education, pp. 159–164, 2019.
  15. K. KišM. Klaučo: Neural Networks Trained as Explicit Tunable MPC Feedback Controllers. Editor(s): M. Fikar and M. Kvasnica, In Proceedings of the 22nd International Conference on Process Control, Slovak Chemical Library, Štrbské Pleso, Slovakia, 2019.
  16. M. KlaučoM. KalúzM. Kvasnica: Machine learning-based warm starting of active set methods in embedded model predictive control. Engineering Applications of Artificial Intelligence, vol. 77, pp. 1–8, 2019.
  17. M. KlaučoM. Kvasnica: MPC-Based Reference Governors, Editor(s): M. J. Grimble, A. Ferrara, Springer, 2019.
  18. M. KlaučoM. Kvasnica: Parametric Optimization with the MPT Toolbox and its Applications in Optimal Control. In 30th European Conference on Operational Research, Dublin, vol. 30, 2019.
  19. M. KvasnicaP. BakaráčM. Klaučo: Complexity reduction in explicit MPC: A reachability approach. Systems & Control Letters, vol. 124, pp. 19–26, 2019.
  20. Y. Lohr – M. KlaučoM. Kalúz – M. Mönnigmann: Mimicking Predictive Control with Neural Networks in Domestic Heating Systems. Editor(s): M. Fikar and M. Kvasnica, In Proceedings of the 22nd International Conference on Process Control, Slovak Chemical Library, Štrbské Pleso, Slovakia, pp. 19–24, 2019.
  21. M. Mojto – K. Ľubušký – M. FikarR. Paulen: Design of Data-based Inferential Sensors for Industrial Depropanizer Column. Editor(s): G. Léonard and F. Logist, In Computer Aided Process Engineering, CAPE Forum, pp. 12–13, 2019.
  22. M. Mojto – K. Ľubušký – R. PaulenM. Fikar: Advanced Process Control of a Depropanizer Column. Editor(s): M. Fikar and M. Kvasnica, In Proceedings of the 22nd International Conference on Process Control, Slovak Chemical Library, Štrbské Pleso, Slovakia, 2019.
  23. M. MojtoR. Paulen – K. Ľubušký – M. Fikar: Modelling and Analysis of Control Pairings of an Industrial Depropanizer Column. In Advanced Process Modelling Forum 26-27 March 2019, pp. 5–6, 2019.
  24. J. OravecM. Bakošová: Collection of Robust Control Examples (in Slovak), Vydavateľstvo FCHPT, FCHPT STU, Radlinského 9, 812 37 Bratislava, 2019.
  25. J. OravecM. Bakošová – L. Galčíková – M. Slávik – M. HorváthováA. Mészáros: Soft-constrained robust model predictive control of a plate heat exchanger: Experimental analysis. Energy, vol. 180, pp. 303–314, 2019.
  26. J. OravecM. BakošováM. Horváthová – L. Galčíková – M. Slávik – A. VasičkaninováA. Mészáros: Convex-lifting-based Robust Control of a Laboratory Plate Heat Exchanger. Chemical Engineering Transactions, vol. 81, pp. 733–738, 2019.
  27. J. Oravec – J. Holaza – M. Horváthová – N. A. Nguyen – M. KvasnicaM. Bakošová: Convex-lifting-based robust control design using the tunable robust invariant sets. European Journal of Control, vol. 49, pp. 44–52, 2019.
  28. R. PaulenM. Fikar: Dynamic real-time optimization of batch processes using Pontryagin’s minimum principle and set-membership adaptation. Computers & Chemical Engineering, vol. 128, pp. 488–495, 2019.
  29. R. PaulenM. Fikar: Dual-Control-Based Approach to Batch Process Operation under Uncertainty Based on Optimality-Conditions Parametrization. Industrial & Engineering Chemistry Research, no. 30, vol. 58, pp. 13508–13516, 2019.
  30. A. Sharma – R. ValoM. KalúzR. PaulenM. Fikar: Implementation of optimal strategy to economically improve batch membrane separation. Journal of Process Control, vol. 76, pp. 155–164, 2019.
  31. J. Su – Y. Zha – K. Wang – M. Villanueva – R. Paulen – B. Houska: Interval Superposition Arithmetic for Guaranteed Parameter Estimation. In 12th IFAC Symposium on Dynamics and Control of Process Systems, including Biosystems DYCOPS 2019, Elsevier, pp. 574–579, 2019.
  32. S. Thangavel – S. Subramanian – R. Paulen – S. Engell: Robust Multi-Stage NMPC under Structural Plant-Model Mismatch without Full-State Measurements. In European Control Conference 2019, IEEE, pp. 781–786, 2019.
  33. C. E. ValeroR. Paulen: Set-Theoretic State Estimation for Multi-output Systems using Block and Sequential Approaches. Editor(s): M. Fikar and M. Kvasnica, In Proceedings of the 22nd International Conference on Process Control, Slovak Chemical Library, Štrbské Pleso, Slovakia, pp. 268–273, 2019.
  34. C. E. ValeroR. Paulen: Effective Recursive Set-membership State Estimation for Robust Linear MPC. In 12th IFAC Symposium on Dynamics and Control of Process Systems, including Biosystems DYCOPS 2019, Elsevier, pp. 486–491, 2019.
  35. P. Valiauga – R. Paulen: Moving-horizon Guaranteed Parameter Estimation: Influence of the Measurement Error. Editor(s): M. Fikar and M. Kvasnica, In Proceedings of the 22nd International Conference on Process Control, Slovak Chemical Library, Štrbské Pleso, Slovakia, pp. 256–261, 2019.
  36. P. Valiauga – R. Paulen: Moving-horizon Guaranteed Parameter Estimation. In 12th IFAC Symposium on Dynamics and Control of Process Systems, including Biosystems DYCOPS 2019, Elsevier, pp. 112–117, 2019.
  37. A. VasičkaninováM. BakošováJ. OravecA. Mészáros: Model Predictive Control of a Tubular Chemical Reactor. Editor(s): M. Fikar and M. Kvasnica, In Proceedings of the 22nd International Conference on Process Control, Slovak Chemical Library, Štrbské Pleso, Slovakia, pp. 228–233, 2019.
  38. M. Villanueva – X. Feng – R. Paulen – B. Chachuat – B. Houska: Convex Enclosures for Constrained Reachability Tubes (in ). In 12th IFAC Symposium on Dynamics and Control of Process Systems, including Biosystems DYCOPS 2019, Elsevier, pp. 118–123, 2019.
  39. K. Wang – Y. Jiang – J. Oravec – M. Villanueva – B. Houska: Parallel Explicit Tube Model Predictive Control. In 58th IEEE Conference on Decision and Control, Nice, France, pp. 7696–7701, 2019.

2018

  1. P. Bakaráč – J. Holaza – M. KlaučoM. Kalúz – J. Löfberg – M. Kvasnica: Explicit MPC based on Approximate Dynamic Programming. In European Control Conference 2018, Limassol, Cyprus, pp. 1172–1177, 2018.
  2. P. BakaráčM. KlaučoM. Fikar: Comparison of Inverted Pendulum Stabilization with PID, LQ, and MPC Control. Editor(s): J. Cigánek, Š. Kozák, A. Kozáková, In 2018 Cybernetics & Informatics (K&I), Slovak Chemical Library, Bratislava, Lazy pod Makytou, Slovakia, vol. 29, 2018.
  3. P. BakaráčM. Kvasnica: Fast nonlinear model predictive control of a chemical reactor: a random shooting approach. Acta Chimica Slovaca, no. 2, vol. 11, pp. 175–181, 2018.
  4. P. Bakaráč – P. Valiauga – M. Kvasnica: Energy-Efficient Swing up and Explicit MPC Stabilization of an Inverted Pendulum. In Preprints of the 6th IFAC Conference on Nonlinear Model Predictive Control, Madison, Wisconsin, USA, 2018.
  5. J. Drgoňa – D. Picard – M. Kvasnica – L. Helsen: Approximate model predictive building control via machine learning. Applied Energy, vol. 218, pp. 199–216, 2018.
  6. J. Holaza – M. Klaučo – J. Drgoňa – J. OravecM. KvasnicaM. Fikar: MPC-Based Reference Governor Control of a Continuous Stirred-Tank Reactor. Computers & Chemical Engineering, vol. 108, pp. 289–299, 2018.
  7. M. KalúzĽ. ČirkaM. Fikar: Flexy: An Open-source Device for Control Education. Editor(s): Cardoso, A., In 13th APCA International Conference on Automatic Control and Soft Computing, Nova Gráfica, Univesrity of the Azores, Ponta Delgada, Portugal, pp. 37–42, 2018.
  8. M. KlaučoM. Kvasnica: Towards On-Line Tunable Explicit MPC Using Interpolation. In Preprints of the 6th IFAC Conference on Nonlinear Model Predictive Control, Madison, Wisconsin, USA, 2018.
  9. M. Kvasnica – C. Jones – I. Pejcic – J. Holaza – M. Korda – P. Bakaráč: Real-Time Implementation of Explicit Model Predictive Control, In Handbook of Model Predictive Control, Editor(s): Sasa V. Rakovic, William S. Levine, Birkhauser, pp. 387–412, 2018.
  10. A. Mészáros – L. Horváth: Contextual Modeling of Engineering Structures Using Organized Content. In 16th International Symposium of Intelligent Systems and Informatics, vol. 16, pp. 105–109, 2018.
  11. I. Mutlu – J. Oravec – F. Schrödel – R. Vosswinkel – M. Bakošová – M. T. Söylemez: Robust Model Predictive Control Based on Stabilizing Parameter Space Calculus. In European Control Conference 2018, Limassol, Cyprus, pp. 206–212, 2018.
  12. J. OravecM. Bakošová – L. Hanulová: Experimental Investigation of Robust MPC Design with Integral Action for a Continuous Stirred Tank Reactor. In 57th IEEE Conference on Decision and Control, Miami, Florida, USA, vol. 57, pp. 2611–2616, 2018.
  13. J. OravecM. Bakošová – L. Hanulová – A. Mészáros: Multivariable Robust Model Predictive Control of a Laboratory Chemical Reactor. Editor(s): Anton Friedl, Jiří J. Klemeš, Stefan Radl, Petar S. Varbanov, Thomas Wallek, In 28th European Symposium on Computer Aided Process Engineering, Elsevier, vol. 28, pp. 961–966, 2018.
  14. J. OravecM. Bakošová – M. Trafczynski – A. VasičkaninováA. Mészáros – M. Markowski: Robust model predictive control and PID control of shell-and-tube heat exchangers. Energy, vol. 159, pp. 1–10, 2018.
  15. J. OravecM. BakošováA. VasičkaninováA. Mészáros: Robust Model Predictive Control of a Plate Heat Exchanger. Chemical Engineering Transactions, vol. 81, pp. 25–30, 2018.
  16. R. PaulenM. Fikar: Dual robust control of batch processes based on optimality-conditions parameterization. In Preprints, 10th IFAC International Symposium on Advanced Control of Chemical Processes Shenyang, Liaoning, China, July 25-27, 2018, Elsevier, pp. 768–773, 2018.
  17. R. Paulen – A. Sharma – M. Fikar: Dynamic Real-time Optimization of Batch Membrane Processes using Pontryagin’s Minimum Principle. Editor(s): Anton Friedl, Jiří J. Klemeš, Stefan Radl, Petar S. Varbanov, Thomas Wallek, In 28th European Symposium on Computer Aided Process Engineering, Elsevier, vol. 28, pp. 1045–1050, 2018.
  18. N. Peric – R. Paulen – M. Villanueva – B. Chachuat: Set-membership nonlinear regression approach to parameter estimation. Journal of Process Control, vol. 70, pp. 80–95, 2018.
  19. U. Sharma – S. Thangavel – A. R. Gottu Mukkula – R. Paulen: Effective Recursive Parallelotopic Bounding for Robust Output-Feedback Control. In 18th IFAC Symposium on System Identification, IFAC, pp. 1032–1035, 2018.
  20. A. Sharma – R. ValoM. KalúzR. PaulenM. Fikar: Experimental validation and comparison of time-optimal and industrial strategy for membrane separation process. In Preprints of the 9th Vienna International Conference on Mathematical Modelling, Vienna, Austria, February 21-23, 2018, pp. 869–874, 2018.
  21. J. Su – Y. Zha – K. Wang – M. Villanueva – R. Paulen – B. Houska: Interval Superposition Arithmetic for Guaranteed Parameter Estimation (in ). 2018.
  22. S. Subramanian – S. Lucia – S. A. Baradaran Birjandi – R. Paulen – S. Engell: A Combined Multi-stage and Tube-based MPC Scheme for Constrained Linear Systems. In Preprints of the 6th IFAC Conference on Nonlinear Model Predictive Control, Madison, Wisconsin, USA, pp. 577–582, 2018.
  23. J. Števek – M. KvasnicaM. Fikar – A. Gomola: A Parametric Programming Approach to Automated Integrated Circuit Design. IEEE Transactions on Control Systems Technology, no. 4, vol. 26, pp. 1180–1191, 2018.
  24. S. Thangavel – M. Aboelnour – S. Lucia – R. Paulen – S. Engell: Robust Dual Multi-stage NMPC using Guaranteed Parameter Estimation. In Preprints of the 6th IFAC Conference on Nonlinear Model Predictive Control, Madison, Wisconsin, USA, pp. 74–79, 2018.
  25. S. Thangavel – S. Lucia – R. Paulen – S. Engell: Dual robust nonlinear model predictive control: A multi-stage approach. Journal of Process Control, vol. 72, pp. 39–51, 2018.

2017

  1. P. BakaráčM. KalúzĽ. Čirka: Design and Development of a Low-cost Inverted Pendulum for Control Education. Editor(s): M. Fikar and M. Kvasnica, In Proceedings of the 21st International Conference on Process Control, Slovak Chemical Library, Štrbské Pleso, Slovakia, pp. 398–403, 2017.
  2. M. BakošováJ. OravecA. VasičkaninováA. Mészáros: Neural-Network-Based and Robust Model-Based Predictive Control of a Tubular Heat Exchanger. Chemical Engineering Transactions, vol. 61, pp. 301–306, 2017.
  3. R. Bousbia-Salah – F. Lesage – M. Fikar – M. A. Latifi: Closed-loop Dynamic Optimization of a Polymer Grafting Batch Reactor. Editor(s): M. Fikar and M. Kvasnica, In Proceedings of the 21st International Conference on Process Control, Slovak Chemical Library, Štrbské Pleso, Slovakia, pp. 376–379, 2017.
  4. J. Drgoňa – M. Klaučo – F. Janeček – M. Kvasnica: Optimal control of a laboratory binary distillation column via regionless explicit MPC. Computers & Chemical Engineering, vol. 96, pp. 139–148, 2017.
  5. J. Drgoňa – Z. Takáč – M. Horňák – R. ValoM. Kvasnica: Fuzzy Control of a Laboratory Binary Distillation Column. Editor(s): M. Fikar and M. Kvasnica, In Proceedings of the 21st International Conference on Process Control, Slovak Chemical Library, Štrbské Pleso, Slovakia, pp. 120–125, 2017.
  6. M. Fikar: Optimal Control of Batch Membrane Processes (in Slovak). Editor(s): Zdeněk Palatý, In Membránové procesy pro udržitelný rozvoj, Česká membránová platforma, z.s, 2017.
  7. A. R. Gottu Mukkula – R. Paulen: Robust model-based design of experiments for guaranteed parameter estimation. Editor(s): Antonio Espuña, Moisès Graells and Luis Puigjaner, In 27th European Symposium on Computer-Aided Process Engineering, Elsevier, pp. 1639–1644, 2017.
  8. J. Holaza – M. KlaučoM. Kvasnica: Solution Techniques for Multi-Layer MPC-Based Control Strategies. In Preprints of the 20th IFAC World Congress, Toulouse, France, vol. 20, 2017.
  9. J. Holaza – R. ValoM. Klaučo: A Novel Approach of Control Design of the pH in the Neutralization Reactor. Editor(s): M. Fikar and M. Kvasnica, In Proceedings of the 21st International Conference on Process Control, Slovak Chemical Library, Štrbské Pleso, Slovakia, pp. 191–196, 2017.
  10. D. Ingole – J. Drgoňa – M. KalúzM. KlaučoM. BakošováM. Kvasnica: Model Predictive Control of a Combined Electrolyzer-Fuel Cell Educational Pilot Plant. Editor(s): M. Fikar and M. Kvasnica, In Proceedings of the 21st International Conference on Process Control, Slovak Chemical Library, Štrbské Pleso, Slovakia, pp. 147–154, 2017.
  11. D. Ingole – J. Drgoňa – M. Kvasnica: Offset-Free Hybrid Model Predictive Control of Bispectral Index in Anesthesia. Editor(s): M. Fikar and M. Kvasnica, In Proceedings of the 21st International Conference on Process Control, Slovak Chemical Library, Štrbské Pleso, Slovakia, pp. 422–427, 2017.
  12. F. Janeček – M. KlaučoM. KalúzM. Kvasnica: OPTIPLAN: A Matlab Toolbox for Model Predictive Control with Obstacle Avoidance. In Preprints of the 20th IFAC World Congress, Toulouse, France, vol. 20, 2017.
  13. F. Janeček – M. KlaučoM. Kvasnica: Trajectory Planning and Following for UAVs with Nonlinear Dynamics. Editor(s): M. Fikar and M. Kvasnica, In Proceedings of the 21st International Conference on Process Control, Slovak Chemical Library, Štrbské Pleso, Slovakia, pp. 333–338, 2017.
  14. M. Jelemenský – M. FikarR. Paulen: Time-Optimal Operation of Membrane Processes in the Presence of Fouling with Set-Membership Parameter Estimation. In Preprints of the 20th IFAC World Congress, Toulouse, France, vol. 20, pp. 4776–4781, 2017.
  15. M. Jelemenský – R. PaulenM. Fikar: Time-optimal Batch Diafiltration under Fouling and Limiting Flux Conditions. In 10th World Congress of Chemical Engineering, vol. 10, 2017.
  16. M. KalúzĽ. ČirkaR. ValoM. Fikar: Lab of Things: A Network-Based I/O Services for Laboratory Experimentation. In Preprints of the 20th IFAC World Congress, Toulouse, France, vol. 20, pp. 14028–14033, 2017.
  17. M. KlaučoM. KalúzM. Kvasnica: Real-time implementation of an explicit MPC-based reference governor for control of a magnetic levitation system. Control Engineering Practice, no. 60, pp. 99–105, 2017.
  18. M. KlaučoM. Kvasnica: Control of a boiler-turbine unit using MPC-based reference governors. Applied Thermal Engineering, vol. 110, pp. 1437–1447, 2017.
  19. M. KlaučoR. Valo – J. Drgoňa: Reflux control of a laboratory distillation column via MPC-based reference governor. Acta Chimica Slovaca, no. 2, vol. 10, pp. 139–143, 2017.
  20. N. A. Nguyen – S. Olaru – P. Rodríguez-Ayerbe – M. Kvasnica: Convex liftings-based robust control design. Automatica, no. March 2017, vol. 77, pp. 206–213, 2017.
  21. J. OravecM. Bakošová – L. Hanulová – M. Horváthová: Design of Robust MPC with Integral Action for a Laboratory Continuous Stirred-Tank Reactor. Editor(s): M. Fikar and M. Kvasnica, In Proceedings of the 21st International Conference on Process Control, Slovak Chemical Library, Štrbské Pleso, Slovakia, pp. 459–464, 2017.
  22. J. OravecM. Bakošová – D. Pakšiová – N. Mikušová – K. Batárová: Advanced Robust MPC Design of a Heat Exchanger: Modeling and Experiments. Editor(s): Antonio Espuña, Moisès Graells, Luis Puigjaner, In 27th European Symposium on Computer Aided Process Engineering, Elsevier, Barcelona, Spain, pp. 1585–1590, 2017.
  23. J. OravecM. Bakošová – P. Valiauga: Advanced Process Control Design for a Distillation Column Using UniSim Design. Editor(s): M. Fikar and M. Kvasnica, In Proceedings of the 21st International Conference on Process Control, Slovak Chemical Library, Štrbské Pleso, Slovakia, pp. 303–308, 2017.
  24. J. Oravec – Y. Jiang – B. Houska – M. Kvasnica: Parallel Explicit MPC for Hardware with Limited Memory. In Preprints of the 20th IFAC World Congress, Toulouse, France, vol. 20, pp. 3356–3361, 2017.
  25. J. OravecM. KlaučoM. Kvasnica – J. Löfberg: Computationally Tractable Formulations for Optimal Path Planning with Interception of Targets’ Neighborhoods. Journal of Guidance, Control, and Dynamics, no. 5, vol. 40, pp. 1221–1230, 2017.
  26. J. OravecM. KvasnicaM. Bakošová: Quasi-Non-Symmetric Input and Output Constraints in LMI-based Robust MPC. In Preprints of the 20th IFAC World Congress, Toulouse, France, vol. 20, pp. 11829–11834, 2017.
  27. J. Oravec – D. Pakšiová – M. BakošováM. Fikar: Soft-Constrained Alternative Robust MPC: Experimental Study. In Preprints of the 20th IFAC World Congress, Toulouse, France, vol. 20, pp. 11877–11882, 2017.
  28. J. Oravec – M. Trafczynski – M. Bakošová – M. Markowski – A. Mészáros – K. Urbaniec: Robust Model Predictive Control of Heat Exchanger Network in the Presence of Fouling. Chemical Engineering Transactions, vol. 61, pp. 334–342, 2017.
  29. A. Sharma – M. Jelemenský – R. PaulenM. Fikar: Optimal Operation of Nanofilter Based Diafiltration Processes Using Experimental Permeation Models. Editor(s): M. Fikar and M. Kvasnica, In Proceedings of the 21st International Conference on Process Control, Slovak Chemical Library, Štrbské Pleso, Slovakia, pp. 185–190, 2017.
  30. A. Sharma – M. Jelemenský – R. PaulenM. Fikar: Modeling and optimal operation of batch closed-loop diafiltration processes. Chemical Engineering Research and Design, vol. 122, pp. 198–210, 2017.

2016

  1. D. Ingole – J. Drgoňa – M. KalúzM. KlaučoM. BakošováM. Kvasnica: Explicit Model Predictive Control of a Fuel Cell. In The European Conference on Computational Optimization, Leuven, Belgium, vol. 4, 2016.
  2. M. Jelemenský – D. Pakšiová – R. Paulen – M. A. Latifi – M. Fikar: Combined Estimation and Optimal Control of Batch Membrane Processes. Processes, no. 4, vol. 4, 2016.
  3. M. Klaučo – S. Blažek – M. Kvasnica: An Optimal Path Planning Problem for Heterogeneous Multi-Vehicle Systems. International Journal of Applied Mathematics and Computer Science, no. 2, vol. 26, pp. 297–308, 2016.
  4. D. Picard – J. Drgoňa – L. Helsen – M. Kvasnica: Impact of the controller model complexity on MPC performance evaluation for building climate control. In The European Conference on Computational Optimization, Leuven, Belgium, vol. 4, 2016.

Investigators

2016

  1. Monika Bakošová
  2. Ľuboš Čirka
  3. Ján Drgoňa
  4. Miroslav Fikar
  5. Juraj Holaza
  6. Deepak Ingole
  7. Filip Janeček
  8. Martin Jelemenský
  9. Martin Kalúz
  10. Martin Klaučo
  11. Michal Kvasnica
  12. Alajos Mészáros
  13. Ján Mikleš
  14. Juraj Oravec
  15. Daniela Pakšiová
  16. Ayush Sharma
  17. Juraj Števek
  18. Richard Valo
  19. Anna Vasičkaninová
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