Project number:
VEGA 1/0585/19
Title of the project:
On-Line Tunable Explicit Model Predictive Control for Systems with a Fast Dynamics
Project type:
VEGA Research Projects
Project duration (start):
01.01.2019
Project duration (end):
31.12.2022
Principal investigator:
Michal Kvasnica
Investigators:
Tereza Ábelová, Peter Bakaráč, Monika Bakošová, Kristína Fedorová, Miroslav Fikar, Matúš Furka, Karol Kiš, Martin Klaučo, Roman Kohút, Juraj Oravec, Petra Valiauga

Period: 1.1.2019 - 31.12.2022

Project Code: VEGA 1/0585/19

Principal investigator: Michal Kvasnica

Scientific co-workers: Martin Klaučo, Miroslav Fikar, Juraj Oravec, Peter Bakaráč

Aims of the project: The aim of the project is the development of a unified methodology for the design, synthesis, and implementation of explicit model predictive controllers that can be tuned on-line by changing the parameters of the cost function and/or of the prediction model. Explicit predictive controllers are known to combine quality and safety of nonlinear control algorithms with the cheap implementation complexity known from linear controllers. Therefore they allow for an optimal and safe regulation of systems with a fast dynamics with time constants in the order of milli- to micro-seconds. Their main drawback, however, is that they cannot be re-tuned on-line. Mitigation of this drawback will lead to extension of the current knowledge in the areas of optimal and predictive control and, more importantly, will enable such controllers to be employed in process automation where quality and safety of control algorithms is of paramount importance. 

Publications

2021

  1. R. Dyrska – R. Mitze – M. FikarM. Kvasnica – M. Mönnigmann: Skipping Optimization Problems in Nonlinear Model Predictive Control by Exploiting Saturation. Editor(s): R. Paulen, M. Fikar and J. Oravec, In Proceedings of the 23rd International Conference on Process Control - Summaries Volume, Slovak Chemical Library, Slovak University of Technology in Bratislava, Radlinského 9, SK812-37, Bratislava, Slovakia, pp. 48–48, 2021.
  2. D. Efremov – T. Haniš – M. Klaučo: Haptic Driver Guidance for Lateral Driving Envelope Protection Using Model Predictive Control. In IEEE Intelligent Vehicles Symposium, IEEE Xplore, Las Vegas, NV, USA, USA, 2021.
  3. K. FedorováR. KohútM. Kvasnica: Streamlining Active Set Method in MPC using Cache Memory. In Preprints of the 7th IFAC Conference on Nonlinear Model Predictive Control, IFAC-PapersOnLine, Bratislava, Slovakia, no. 6, vol. 54, 2021.
  4. M. FurkaK. KišP. BakaráčM. Klaučo: Nonlinear MPC Policy for Systems with Data Driven Identification. In Proceedings of the 7th IFAC Conference on Nonlinear Model Predictive Control, IFAC-PapersOnline, no. 54, 2021.
  5. M. FurkaK. KišM. KlaučoM. Kvasnica: Usage of Homomorphic Encryption Algorithms in Process Control. Editor(s): R. Paulen and M. Fikar, In Proceedings of the 23rd International Conference on Process Control, IEEE, Slovak University of Technology, pp. 43–48, 2021.
  6. M. Horváthová – N. Ishihara – J. Oravec – Y. Chida: Robust Setpoint Tracking of a Linear System with Discrete Actuators. Editor(s): R. Paulen and M. Fikar, In Proceedings of the 23rd International Conference on Process Control, IEEE, Slovak University of Technology, pp. 229–236, 2021.
  7. Y. Jiang – J. Oravec – B. Houska – M. Kvasnica: Parallel MPC for Linear Systems with Input Constraints. IEEE Transactions on Automatic Control, no. 7, vol. 66, pp. 3401–3408, 2021.
  8. K. KišM. KlaučoM. Kvasnica: Explicit MPC in the form of Sparse Neural Networks. Editor(s): R. Paulen and M. Fikar, In Proceedings of the 23rd International Conference on Process Control, IEEE, Slovak University of Technology, pp. 163–168, 2021.
  9. R. KohútL. GalčíkováK. FedorováT. ÁbelováM. BakošováM. Kvasnica: Hidden Markov Model-based Warm-start of Active Set Method in Model Predictive Control. Editor(s): R. Paulen and M. Fikar, In Proceedings of the 23rd International Conference on Process Control, IEEE, Slovak University of Technology, 2021.
  10. M. MojtoM. HorváthováK. KišM. FurkaM. Bakošová: Predictive control of a cascade of biochemical reactors. Acta Chimica Slovaca, no. 1, vol. 14, pp. 51–59, 2021.

2020

  1. P. BakaráčM. KlaučoJ. OravecM. Furka: Microcontroller platform with embedded dynamic process (in Slovak). 2020.
  2. M. FurkaK. KišM. HorváthováM. MojtoM. Bakošová: Identification and Control of a Cascade of Biochemical Reactors. In 2020 Cybernetics & Informatics (K&I), 2020.
  3. J. Holaza – J. OravecM. Kvasnica – R. Dyrska – M. Mönnigmann – M. Fikar: Accelerating Explicit Model Predictive Control by Constraint Sorting. Editor(s): Rolf Findeisen, Sandra Hirche, Klaus Janschek, Martin Mönnigmann, 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: Real-Time Convex-lifting-based Robust Control Using Approximated Control Law. In 59th IEEE Conference on Decision and Control, Jeju Island, Republic of Korea, vol. 59, pp. 2160–2165, 2020.
  5. C. Jugade – D. Ingole – D. Sonawane – M. Kvasnica – J. Gustafson: A Framework for Embedded Model Predictive Control using Posits. In 59th IEEE Conference on Decision and Control, Jeju Island, Republic of Korea, vol. 59, pp. 2509–2514, 2020.
  6. 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.
  7. M. Kvasnica: Learning More from Less Data: When Quality Trumps Quantity (Workshop at IFAC World Congress 2020). 2020.
  8. M. Kvasnica: Low-Complexity Model Predictive Control for Systems with a Fast Dynamics. Editor(s): I. Petráš, J. Kačur, In Proceedings of the 2020 21st International Carpathian Control Conference (ICCC), IEEE, 2020.
  9. Y. Lohr – M. KlaučoM. Fikar – M. Mönnigmann: Machine Learning Assisted Solutions of Mixed Integer MPC on Embedded Platforms. Editor(s): Rolf Findeisen, Sandra Hirche, Klaus Janschek, Martin Mönnigmann, In Preprints of the 21st IFAC World Congress (Virtual), Berlin, Germany, July 12-17, 2020, vol. 21, 2020.
  10. L. Lu – M. Kvasnica: Low-Complexity Stabilizing PWA Controllers for Linear Systems with Parametric Uncertainties. Editor(s): Rolf Findeisen, Sandra Hirche, Klaus Janschek, Martin Mönnigmann, In Preprints of the 21st IFAC World Congress (Virtual), Berlin, Germany, July 12-17, 2020, vol. 21, pp. 7376–7381, 2020.
  11. A. Schirrer – T. Haniš – M. Klaučo – S. Thormann – M. Hromčík – S. Jakubek: Safety-extended Explicit MPC for Autonomous Truck Platooning on Varying Road Conditions. Editor(s): Rolf Findeisen, Sandra Hirche, Klaus Janschek, Martin Mönnigmann, In Preprints of the 21st IFAC World Congress (Virtual), Berlin, Germany, July 12-17, 2020, vol. 21, 2020.
  12. 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.

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. Chemical papers, no. 3, vol. 73, pp. 611–618, 2019.
  3. K. FedorováP. 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.
  4. K. FedorováP. BakaráčM. Kvasnica: Agile Manoeuvres using Model Predictive Control. Acta Chimica Slovaca, no. 1, vol. 12, pp. 136–141, 2019.
  5. 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.
  6. 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.
  7. 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.
  8. K. KišM. Klaučo: Neural network based explicit MPC for chemical reactor control. Acta Chimica Slovaca, no. 2, vol. 12, pp. 218–223, 2019.
  9. M. KlaučoM. Kvasnica: MPC-Based Reference Governors, Editor(s): M. J. Grimble, A. Ferrara, Springer, 2019.
  10. 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.
  11. M. KvasnicaP. BakaráčM. Klaučo: Complexity reduction in explicit MPC: A reachability approach. Systems & Control Letters, vol. 124, pp. 19–26, 2019.
  12. J. OravecM. BakošováL. 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.
  13. J. OravecM. BakošováM. HorváthováL. 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.
  14. 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.
  15. 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.

Investigators


Responsibility for content: Ing. MSc. Martin Klaučo, PhD.
Last update: 21.12.2018 12:45
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