Position:
Lecturer
Researcher
PhD student
Department:
Department of Information Engineering and Process Control (DIEPC)
Room:
NB 633
eMail:
Home page:
https://www.uiam.sk/~kis
Phone:
+421 259 325 176
ORCID iD:
0000-0002-8294-9871
WoS ResearcherID:
ABD-4372-2020
Google Scholar:
MgqCvIoAAAAJ
Availability:

Publications

Article in journal

  1. J. Drgoňa – K. Kiš – A. Tuor – D. Vrabie – M. Klaučo: Differentiable predictive control: Deep learning alternative to explicit model predictive control for unknown nonlinear systems. Journal of Process Control, vol. 116, pp. 80–92, 2022.
  2. M. Mojto – M. HorváthováK. Kiš – M. Furka – M. Bakošová: Predictive control of a cascade of biochemical reactors. Acta Chimica Slovaca, no. 1, vol. 14, pp. 51–59, 2021.
  3. K. KišM. Klaučo: Neural network based explicit MPC for chemical reactor control. Acta Chimica Slovaca, no. 2, vol. 12, pp. 218–223, 2019.

Article in conference proceedings

  1. M. FikarK. KišM. Klaučo – M. Mönnigmann: Simple Tuning of Arbitrary Controllers using Governors. In IFAC World Congress 2023, Yokohama, Japan, pp. 9109–9114, 2023.     Zenodo
  2. K. KišM. Klaučo: Nearly-optimal Explicit MPC-based Reference Governors with Long Prediction Horizons Generated with Machine Learning. 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.
  3. M. Furka – K. KišM. Klaučo: Control of a Chemical Reactor with High Precision Encryption Framework. In 2022 Cybernetics & Informatics (K&I), pp. 1–6, 2022.
  4. K. KišP. BakaráčM. Klaučo: Nearly Optimal Tunable MPC Strategies on Embedded Platforms. In 18th IFAC Workshop on Control Applications of Optimization, IFAC-PapersOnline, pp. 326–331, 2022.
  5. M. Fikar – M. Furka – M. HorváthováK. Kiš – M. Mojto: Dynamic Optimisation Toolbox dynopt 5.0. Editor(s): R. Paulen and M. Fikar, In Proceedings of the 23rd International Conference on Process Control, IEEE, Slovak University of Technology, pp. 296–301, 2021.
  6. M. Furka – K. 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.
  7. M. Furka – K. 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.
  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. M. Furka – K. KišM. Horváthová – M. Mojto – M. Bakošová: Identification and Control of a Cascade of Biochemical Reactors. In 2020 Cybernetics & Informatics (K&I), 2020.
  10. 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.
  11. 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.

Phd's thesis

  1. K. Kiš: Machine Learning Based Process Control. ÚIAM FCHPT STU v Bratislave, Radlinského 9, 812 37 Bratislava, 2023.

Master's thesis

  1. K. Kiš: Machine Learning Approaches Applied to Generation of Explicit Control Laws. Master's thesis, ÚIAM FCHPT STU v Bratislave, Radlinského 9, 812 37 Bratislava, 2019.

Bachelor's thesis

  1. K. Kiš: Creation of a remote SCADA/HMI for a laboratory batch membrane process station experiment. (in Slovak). Bachelor's thesis, ÚIAM FCHPT STU v Bratislave, Radlinského 9, 812 37 Bratislava, 2017.

Miscellaneous

  1. M. FikarM. KlaučoK. Kiš: A General Controller Tuning using Governors. 2022.
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