Institute of Information Engineering, Automation, and Mathematics

Ing. Martin Kalúz, PhD.

Position:
Researcher
Technician
Department:
Department of Information Engineering and Process Control (DIEPC)
Room:
NB 666
eMail:
Home page:
https://www.uiam.sk/~kaluz
Phone:
+421 259 325 355
ORCID iD:
0000-0001-6654-6354
WoS ResearcherID:
AAZ-3590-2020
Google Scholar:
L3WRrsUAAAAJ
Research activities:
Information technologies
Availability:

Citations

  • Total citations       350
M. Kalúz – Ľ. Čirka – M. Fikar: ELab: A Lightweight SCADA System for Control Engineering Research and Education. 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. 17469–17474, 2020.
  • Number of citations       3
  • Lei, X.: Network education integrated system based on intelligent algorithm. In Proceedings of SPIE - The International Society for Optical Engineering, 2023.
  • Hou, Q.: Design of a Visual Training System for Software Engineering Education Based on Knowledge Graphs. International Journal of Emerging Technologies in Learning, no. 24, vol. 17, pp. 114-130, 2022.
  • Mirdanies, M. – Yazid, E. – Ardiansyah, R.A. – Sulaeman, Y.: The Development of Human Machine Interface (HMI) Based Graphical User Interface (GUI) for Telecontrol System of a Ship Mounted Two-DoF Manipulator. In Proceeding - 2022 International Conference on Radar, Antenna, Microwave, Electronics, and Telecommunications: Emerging Science and Industrial Innovation in Electronics and Telecommunication, ICRAMET 2022, pp. 212-218, 2022.
M. Kalúz – M. Klaučo – Ľ. Čirka – M. Fikar: Flexy2: A Portable Laboratory Device for Control Engineering Education. In 12th IFAC Symposium Advances in Control Education, pp. 159–164, 2019.
  • Number of citations       8
  • Marin, Loreto – Vargas, Hector – Heradio, Ruben – de la Torre, Luis – Diaz, Jose Manuel – Dormido, Sebastian: Evidence-Based Control Engineering Education: Evaluating the LCSD Simulation Tool. IEEE Access, vol. 8, pp. 170183-170194, 2020.
  • J. L. Villa – S. Sanchez: Implementing a Software-based Controller as a Strategy for Teaching Digital Control. In 2020 IX International Congress of Mechatronics Engineering and Automation (CIIMA), pp. 1-6, 2020.
  • Opris, Ioana – Gogoase Nistoran, Daniela E. – Costinas, Sorina – Ionescu, Cristina S.: Rethinking power engineering education for Generation Z. Computer Applications in Engineering Education, no. 1, SI, vol. 29, pp. 287-305, 2021.
  • Dusek, F. – Honc, D. – Mrazek, M.: RCDue - Laboratory System for Teaching Automation and Control - Concept of the system. In Proceedings of the 2021 23rd International Conference on Process Control, PC 2021, pp. 249-254, 2021.
  • Sotelo, David – Sotelo, Carlos – Ramirez-Mendoza, Ricardo A. – Lopez-Guajardo, Enrique A. – Navarro-Duran, David – Nino-Juarez, Elvira – Vargas-Martinez, Adriana: Lab-Tec@Home: A Cost-Effective Kit for Online Control Engineering Education. Electronics, no. 6, vol. 11, 2022.
  • Oliveira, P. B. de Moura – Soares, Filomena – Cardoso, Alberto: Pocket-Sized Portable Labs: Control Engineering Practice Made Easy in Covid-19 Pandemic Times. Ifac Papersonline, no. 17, vol. 55, pp. 150-155, 2022.
  • Pajpach, Martin – Haffner, Oto – Kucera, Erik – Drahos, Peter: Low-Cost Education Kit for Teaching Basic Skills for Industry 4.0 Using Deep-Learning in Quality Control Tasks. Electronics, no. 2, vol. 11, 2022.
  • Cardoso, Alberto – Oliveira, Paulo Moura – Sa, Joao: Pocket Labs as a STEM Learning Tool and for Engineering Motivation. In Learning in the Age of Digital and Green Transition, Icl2022, Vol 1, pp. 413-422, 2023.
Y. Lohr – M. Klaučo – M. 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.
  • Number of citations       1
  • M. Furka – K. Kiš – M. Horváthová – M. Mojto – M. Bakošová: Identification and Control of a Cascade of Biochemical Reactors. In 2020 Cybernetics Informatics (K I), pp. 1-6, 2020.
A. Sharma – R. Valo – M. Kalúz – R. Paulen – M. Fikar: Implementation of optimal strategy to economically improve batch membrane separation. Journal of Process Control, vol. 76, pp. 155–164, 2019.
  • Number of citations       3
  • Wu, Xiaolong – Han, Honggui – Qiao, Junfei: Data-Driven Intelligent Warning Method for Membrane Fouling. IEEE Transactions on Neural Networks and Learning Systems, no. 8, vol. 32, pp. 3318-3329, 2021.
  • Wu, Xiao-Long – Han, Hong-Gui – Zhang, Hui-Juan – Qiao, Jun-Fei: Intelligent Warning of Membrane Fouling Based on Robust Deep Neural Network. International Journal of Fuzzy Systems, 2021.
  • Trystram,G.: Automatic control of industrial food processes, pp. 351-390, 2022.
M. Klaučo – M. Kalúz – M. 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.
  • Number of citations       28
  • Masti, Daniele – Bemporad, Alberto: Learning binary warm starts for multiparametric mixed-integer quadratic programming. In 2019 18th European Control Conference (ECC), pp. 1494-1499, 2019.
  • Nouwens, S.A.N. – de Jager, B. – Paulides, M. – Heemels, W.P.M.H.: Constraint-adaptive MPC for large-scale systems: Satisfying state constraints without imposing them. In IFAC-PapersOnLine, pp. 232-237, 2021.
  • Schwenkel, Lukas – Gharbi, Meriem – Trimpe, Sebastian – Ebenbauer, Christian: Online learning with stability guarantees: A memory-based warm starting for real-time MPC. Automatica, no. 109247, vol. 122, 2020.
  • Sabir, Zulqurnain – Raja, Muhammad Asif Zahoor – Guirao, Juan L. G. – Shoaib, Muhammad: Integrated intelligent computing with neuro-swarming solver for multi-singular fourth-order nonlinear Emden-Fowler equation. Computational & Applied Mathematics, no. 4, vol. 39, 2020.
  • Vaupel, Yannic – Hamacher, Nils C. – Caspari, Adrian – Mhamdi, Adel – Kevrekidis, Ioannis G. – Mitsos, Alexander: Accelerating nonlinear model predictive control through machine learning. Journal of Process Control, no. NM0HO, vol. 92, pp. 261-270, 2020.
  • Bertsimas, Dimitris – Stellato, Bartolomeo: The voice of optimization. Machine Learning, no. MM4AL, 2020.
  • Umar, Muhammad – Sabir, Zulqurnain – Amin, Fazli – Guirao, Juan L. G. – Raja, Muhammad Asif Zahoor: Stochastic numerical technique for solving HIV infection model of CD4(+) T cells. European Physical Journal Plus, no. 6, vol. 135, 2020.
  • Leal, Adonis F. R. – Rakov, V. A. – Alves, Elton Rafael – Lopes, Marcio N. G.: Estimation of -CG lightning distances using single-station E-field measurements and machine learning techniques. In 2019 International Symposium on Lightning Protection (xv Sipda), 2019.
  • Ihtesham Jadoon – Ashfaq Ahmed – Ata ur Rehman – Muhammad Shoaib – Muhammad Asif Zahoor Raja: Integrated meta-heuristics finite difference method for the dynamics of nonlinear unipolar electrohydrodynamic pump flow model. Applied Soft Computing, vol. 97, pp. 106791, 2020.
  • Umar, M. – Sabir, Z. – Raja, M.A.Z. – Sánchez, Y.G.: A stochastic numerical computing heuristic of SIR nonlinear model based on dengue fever. Results in Physics, no. 103585, vol. 19, 2020.
  • Li, Z. – Xu, H.: Analysis of Working Characteristics of Buck Converter in Artificial Intelligence Background. Advances in Intelligent Systems and Computing (Conference Paper), vol. 1088, pp. 529-537, 2020.
  • Sabir, Z. – Nisar, K. – Zahoor Raja, M.A. – Haque, M.R. – Umar, M. – Ag Ibrahim, A.A. – Le, D.-N.: IoT Technology Enabled Heuristic Model with Morlet Wavelet Neural Network for Numerical Treatment of Heterogeneous Mosquito Release Ecosystem. IEEE Access, vol. 9, pp. 132897-132913, 2021.
  • Bertsimas, D. – Stellato, B.: The voice of optimization. Machine Learning, no. 2, vol. 110, pp. 249-277, 2021.
  • Sabir, Z. – Khalique, C.M. – Raja, M.A.Z. – Baleanu, D.: Evolutionary computing for nonlinear singular boundary value problems using neural network, genetic algorithm and active-set algorithm. European Physical Journal Plus, no. 2, vol. 136, 2021.
  • Stomberg, G. – Engelmann, A. – Faulwasser, T.: A distributed active set method for model predictive control. In IFAC-PapersOnLine, pp. 263-268, 2021.
  • Liu, W. – Zheng, Y. – Chen, Q. – Geng, D.: An adaptive CGPC based anti-windup PI controller with stability constraints for the intermittent power penetrated system. International Journal of Electrical Power and Energy Systems, no. 106922, vol. 130, 2021.
  • Sabir, Z. – Ag Ibrahim, A.A. – Raja, M.A.Z. – Nisar, K. – Umar, M. – Rodrigues, J.J.P.C. – Mahmoud, S.R.: Soft computing paradigms to find the numerical solutions of a nonlinear influenza disease model. Applied Sciences (Switzerland), no. 18, vol. 11, 2021.
  • Hu, W. – Zhou, Y. – Zhang, Z. – Fujita, H.: Model Predictive Control for Hybrid Levitation Systems of Maglev Trains with State Constraints. IEEE Transactions on Vehicular Technology, no. 10, vol. 70, pp. 9972-9985, 2021.
  • Norouzi, A. – Heidarifar, H. – Shahbakhti, M. – Koch, C.R. – Borhan, H.: Model predictive control of internal combustion engines: A review and future directions. Energies, no. 19, vol. 14, 2021.
  • Sabir, Z. – Raja, M.A.Z. – Baleanu, D. – Cengiz, K. – Shoaib, M.: Design of Gudermannian Neuroswarming to solve the singular Emden–Fowler nonlinear model numerically. Nonlinear Dynamics, no. 4, vol. 106, pp. 3199-3214, 2021.
  • Ławryńczuk, M.: Introduction to Model Predictive Control. Studies in Systems, Decision and Control, vol. 389, pp. 3-40, 2022.
  • Chen, S.W. – Wang, T. – Atanasov, N. – Kumar, V. – Morari, M.: Large scale model predictive control with neural networks and primal active sets. Automatica, no. 109947, vol. 135, 2022.
  • Sabir, Z. – Raja, M.A.Z. – Botmart, T. – Weera, W.: A Neuro-Evolution Heuristic Using Active-Set Techniques to Solve a Novel Nonlinear Singular Prediction Differential Model. Fractal and Fractional, no. 1, vol. 6, 2022.
  • Liu, Qibo – Li, Shaoyuan – Zheng, Yi – Qi, Chenkun – Luo, Min: Learning-Based Distributed Model Predictive Control Approximation Scheme With Guarantees. IEEE Transactions on Industrial Informatics, 2023.
  • Sabir, Zulqurnain – Baleanu, Dumitru – Alhazmi, Sharifah E. – Ben Said, Salem: Heuristic computing with active set method for the nonlinear Rabinovich-Fabrikant model. Heliyon, no. 11, vol. 9, 2023.
  • Emori, E. Y. – Ravagnani, M. A. S. S. – Costa, C. B. B.: An Advanced Control Strategy for the Evaporation Section of An Integrated First- and Second-Generation Ethanol Sugarcane Biorefinery. Chemical and Biochemical Engineering Quarterly, no. 1, vol. 37, pp. 17-32, 2023.
  • Leonow, Sebastian – Dyrska, Raphael – Moennigmann, Martin: Embedded Implementation of a Neural Network emulating Nonlinear MPC in a process control application. In 2023 European Control Conference, ECC, 2023.
  • Norouzi, Armin – Heidarifar, Hamed – Borhan, Hoseinali – Shahbakhti, Mahdi – Koch, Charles Robert: Integrating Machine Learning and Model Predictive Control for automotive applications: A review and future directions. Engineering Applications of Artificial Intelligence, no. 105878, vol. 120, 2023.
P. Bakaráč – J. Holaza – M. Klaučo – M. Kalúz – J. Löfberg – M. Kvasnica: Explicit MPC based on Approximate Dynamic Programming. In European Control Conference 2018, Limassol, Cyprus, pp. 1172–1177, 2018.
  • Number of citations       8
  • Moennigmann, Martin: On the structure of the set of active sets in constrained linear quadratic regulation. Automatica, vol. 106, pp. 61-69, 2019.
  • Gulan, M. – Minarcik, P. – Kulhanek, J.: Energy-efficient Swing-up and MPC Stabilization of an Inverted Pendulum. In Proceedings of the 2019 22nd International Conference on Process Control, PC 2019, pp. 209-214, 2019.
  • Boumaza, H. – Belarbi, K.: Optimal model predictive control solution approximation using Takagi Sugeno for linear and a class of nonlinear systems. International Journal of Dynamics and Control, 2021.
  • Teófilo P. G. Mendes – Leizer Schnitman – Idelfonso Bessa dos Reis Nogueira – Ana Mafalda Almeida Peixoto Ribeiro – Alírio Egídio Rodrigues – José Miguel Loureiro – Márcio A.F. Martins: A new Takagi-Sugeno-Kang model-based stabilizing explicit MPC formulation: An experimental case study with implementation embedded in a PLC. Expert Systems with Applications, vol. 210, pp. 118369, 2022.
  • Gupta, Nikita – De, Riju – Kodamana, Hariprasad – Bhartiya, Sharad: Batch-to-Batch Adaptive Iterative Learning Control─ Explicit Model Predictive Control Two-Tier Framework for the Control of Batch Transesterification Process. ACS omega, no. 45, vol. 7, pp. 41001–41012, 2022.
  • Tijani, Tunde Mufutau – Jimoh, Isah Abdulrasheed: Optimal control of the double inverted pendulum on a cart: A comparative study of explicit MPC and LQR. Applications of Modelling and Simulation, vol. 5, pp. 74–87, 2021.
  • Aouaichia, Abdelhadi – Kara, Kamel – Benrabah, Mohamed – Hadjili, Mohamed Laid: Constrained Neural Network Model Predictive Controller Based on Archimedes Optimization Algorithm with Application to Robot Manipulators. Journal of Control, Automation and Electrical Systems, no. 6, vol. 34, pp. 1159–1178, 2023.
  • Srishti – Sharma, Sudeep – Padhy, Prabin K: Comparative Study of Inverted Pendulum with Various Types of Controllers. In 2021 International Conference on Control, Automation, Power and Signal Processing (CAPS), pp. 1-5, 2021.
M. Kalúz – Ľ. Čirka – M. 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.
  • Number of citations       7
  • Demenkov, M.: Experimental Investigation of Viscoelastic Hysteresis in a Flex Sensor. Trends in Mathematics, vol. 11, pp. 231-235, 2019.
  • Oravec, J. – Holaza, J. – Horváthová, M. – Nguyen, N.A. – Kvasnica, M. – Bakošová, M.: Convex-lifting-based robust control design using the tunable robust invariant sets. European Journal of Control, vol. 49, pp. 44-52, 2019.
  • Takács, G. – Konkoly, T. – Gulan, M.: OptoShield: A Low-Cost Tool for Control and Mechatronics Education. In 2019 12th Asian Control Conference, ASCC 2019, pp. 1001-1006, 2019.
  • Takács, G. – Gulan, M. – Bavlna, J. – Köplinger, R. – Kováč, M. – Mikuláš, E. – Zarghoon, S. – Salíni, R.: HeatShield: A low-cost didactic device for control education simulating 3d printer heater blocks. In IEEE Global Engineering Education Conference, EDUCON, pp. 374-383, 2019.
  • Demenkov, M.: Studying aeroelastic oscillations with tensoresistor and Arduino. In AIP Conference Proceedings, 2018.
  • Afonso, Ricardo – Soares, Filomena – de Moura Oliveira, P. B.: Innovative Teaching/Learning Methodologies in Control, Automation and Robotics: a Short Review. In 2021 4th International Conference of the Portuguese Society for Engineering Education (cispee), 2021.
  • Horvathova, Michaela – Oravec, Juraj – Bakosova, Monika: Real-Time Convex-lifting-based Robust Control Using Approximated Control Law. In 2020 59th IEEE Conference on Decision and Control (CDC), pp. 2160-2165, 2020.
A. Sharma – R. Valo – M. Kalúz – R. Paulen – M. 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.
  • Number of citations       2
  • Melnikova, Elena – Bogdanova, Ekaterina – Paveleva, Daria: The Research of Whey Permeate Mineral Profile at Different Stages of Membrane Filtration. Potravinarstvo Slovak Journal of Food Sciences, vol. 17, pp. 748 – 758, 2023.
  • Melnikova, Elena Ivanovna – Bogdanova, Ekaterina Viktorovna – Paveleva, Daria Anatolyevna: Whey Permeate Mineral Profile at Various Stages of Membrane Filtration; [مشخصات مواد معدنی تراویده آب پنیر در مراحل گوناگون تصفیه غشایی]. Applied Food Biotechnology, no. 4, vol. 10, pp. 223 – 231, 2023.
A. Vasičkaninová – M. Bakošová – Ľ. Čirka – M. Kalúz – J. Oravec: Robust Controller Design for a Laboratory Heat Exchanger. Applied Thermal Engineering, vol. 128, pp. 1297–1309, 2018.
  • Number of citations       15
  • Petar Sabev Varbanov – Xue Xiu Jia – David John Kukulka – Xia Liu – Jiří Jaromír Klemeš: Emission minimisation by improving heat transfer, energy conversion, CO2 integration and effective training. Applied Thermal Engineering, vol. 131, pp. 531–539, 2018.
  • Bartecki, Krzysztof: Rational Transfer Function Model for a Double-Pipe Parallel-Flow Heat Exchanger. Symmetry-basel, no. 8, vol. 12, 2020.
  • LiborPekař: Advanced Analytic and Control Techniques for Thermal Systems with Heat Exchangers, Chapter: Chapter 12 - Controller design and tuning of a delayed heat exchanger plant in a robust sense. pp. 263-284, 2020.
  • Greco, Adriana – Gundabattini, Edison – Solomon, Darius Gnanaraj – Rassiah, Raja Singh – Masselli, Claudia: A Review on Geothermal Renewable Energy Systems for Eco-Friendly Air-Conditioning. Energies, no. 15, vol. 15, 2022.
  • Zhu, Jianzhong – Wu, Xiao – Shen, Jiong: Practical disturbance rejection control for boiler-turbine unit with input constraints. Applied Thermal Engineering, no. 114184, vol. 161, 2019.
  • Sallam, Omar Khaled – Azar, Ahmad Taher – Guaily, Amr – Ammar, Hossam Hassan: Tuning of PID Controller Using Particle Swarm Optimization for Cross Flow Heat Exchanger Based on CFD System Identification. In Proceedings of the International Conference on Advanced Intelligent Systems and Informatics 2019, pp. 300-312, 2020.
  • Chen, Yilong – de Oliveira, Mauricio C.: An Alternative Algorithm to the D-K Iterations for Robust Control Design. IEEE Control Systems Letters, no. 1, vol. 5, pp. 115-120, 2021.
  • Bartecki, Krzysztof: An Approximate Transfer Function Model for a Double-Pipe Counter-Flow Heat Exchanger. Energies, no. 14, vol. 14, 2021.
  • Jin, Hao-Zhe – Gu, Yong – Ou, Guo-Fu: Corrosion risk analysis of tube-and-shell heat exchangers and design of outlet temperature control system. Petroleum Science, no. 4, vol. 18, pp. 1219-1229, 2021.
  • Yong Gu – Hao-Zhe Jin – Guo-Fu Ou: Corrosion risk analysis of tube-and-shell heat exchangers and design of outlettemperature control system. Petroleum Science, 2021.
  • Sit, M. L. – Patsiuk, I, V. – Juravliov, A. A. – Burciu, I, V. – Timchenko, V, D.: Control of Heat Exchanger with Variable Heat Transfer Surface Area. Problemele Energeticii Regionale, no. 1, pp. 90-101, 2019.
  • Wen, Yalan – Wang, Ling – Peng, Weiqing – Menhas, Muhammad Ilyas – Qian, Lin: Application of Intelligent Virtual Reference Feedback Tuning to Temperature Control in a Heat Exchanger. In Intelligent Computing and Internet of Things, Pt Ii, pp. 311-320, 2018.
  • Bartecki, Krzysztof: Rational Transfer Function Model for a Double-Pipe Parallel-Flow Heat Exchanger. Symmetry-basel, no. 8, vol. 12, 2020.
  • Govind, Achu K. R. – Subhasish, Mahapatra: Design of PI/PID Control Algorithm for a Benchmark Heat Exchanger System using Frequency Domain Specifications. In 2022 IEEE International Power and Renewable Energy Conference, Iprecon, 2022.
  • Pekar, Libor – Matusu, Radek – Dostalek, Petr – Song, Mengjie: Further experimental results on modelling and algebraic control of a delayed looped heating-cooling process under uncertainties. Heliyon, no. 8, vol. 9, 2023.
M. Kalúz – Ľ. Čirka – R. Valo – M. 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.
  • Number of citations       3
  • M. D. Prieto – Á. F. Sobrino – L. R. Soto – D. Romero – P. F. Biosca – L. R. Martínez: Active Learning based Laboratory towards Engineering Education 4.0. In 2019 24th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA), pp. 776-783, 2019.
  • Juraj Oravec – Monika Bakošová – Lenka Galčíková – Michal Slávik – Michaela Horváthová – Alajos Mészáros: Soft-constrained robust model predictive control of a plate heat exchanger: Experimental analysis. Energy, vol. 180, pp. 303 - 314, 2019.
  • R. Dyrska – M. Horváthová – P. Bakaráč – M. Mönnigmann – J. Oravec: Heat exchanger control using model predictive control with constraint removal. Applied Thermal Engineering, vol. 227, 2023.   Zenodo
F. Janeček – M. Klaučo – M. Kalúz – M. 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.
  • Number of citations       9
  • Ioan, Daniel – Olaru, Sorin – Prodan, Ionela – Stoican, Florin – Niculescu, Silviu-Iulian: Navigation in a multi-obstacle environment. From partition of the space to a zonotopic-based MPC. In 2019 18th European Control Conference (ECC), pp. 1772-1777, 2019.
  • Stoican, Florin – Prodan, Ionela – Grotli, Esten Ingar: Exact and overapproximated guarantees for corner cutting avoidance in a multiobstacle environment. International Journal of Robust and Nonlinear Control, no. 15, vol. 28, pp. 4528-4548, 2018.
  • Ioan, D. – Prodan, I. – Stoican, F. – Olaru, S. – Niculescu, S.-I.: Complexity bounds for obstacle avoidance within a zonotopic framework. In Proceedings of the American Control Conference, pp. 335-340, 2019.
  • Ioan, D. – Olaru, S. – Prodan, I. – Stoican, F. – Niculescu, S.-I.: Parametrized Hyperplane Arrangements for Control Design with Collision Avoidance Constraints. In IEEE International Conference on Control and Automation, ICCA, pp. 1591-1596, 2019.
  • Ioan, D. – Prodan, I. – Olaru, S. – Stoican, F. – Niculescu, S.-I.: Mixed-integer programming in motion planning. Annual Reviews in Control, 2020.
  • Ioan, D. – Olaru, S. – Prodan, I. – Stoican, F. – Niculescu, S.-I.: From Obstacle-Based Space Partitioning to Corridors and Path Planning. A Convex Lifting Approach. IEEE Control Systems Letters, no. 1, vol. 4, pp. 79-84, 2020.
  • Reiter, R. – Kirchengast, M. – Watzenig, D. – Diehl, M.: Mixed-integer optimization-based planning for autonomous racing with obstacles and rewards. In IFAC-PapersOnLine, pp. 99-106, 2021.
  • Kochdumper, N. – Gruber, F. – Schürmann, B. – Gaßmann, V. – Klischat, M. – Althoff, M.: AROC: A toolbox for automated reachset optimal controller synthesis. In HSCC 2021 - Proceedings of the 24th International Conference on Hybrid Systems: Computation and Control (part of CPS-IoT Week), 2021.
  • Ioan, D. – Prodan, I. – Olaru, S. – Stoican, F. – Niculescu, S.-I.: Mixed-integer programming in motion planning. Annual Reviews in Control, vol. 51, pp. 65-87, 2021.
D. Ingole – J. Drgoňa – M. Kalúz – M. Klaučo – M. Bakošová – M. 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.
  • Number of citations       1
  • Koundi, Mohamed – El Fadil, Hassan – EL Idrissi, Zakaria – Lassioui, Abdellah – Intidam, Abdessamad – Bouanou, Tasnime – Nady, Soukaina – Rachid, Aziz: Investigation of Hydrogen Production System-Based PEM EL: PEM EL Modeling, DC/DC Power Converter, and Controller Design Approaches. Clean Technologies, no. 2, vol. 5, pp. 531–568, 2023.
P. Bakaráč – M. Kalúz – Ľ. 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.
  • Number of citations       7
  • Takács, G. – Konkoly, T. – Gulan, M.: OptoShield: A Low-Cost Tool for Control and Mechatronics Education. In 2019 12th Asian Control Conference, ASCC 2019, pp. 1001-1006, 2019.
  • Takács, G. – Gulan, M. – Bavlna, J. – Köplinger, R. – Kováč, M. – Mikuláš, E. – Zarghoon, S. – Salíni, R.: HeatShield: A low-cost didactic device for control education simulating 3d printer heater blocks. In IEEE Global Engineering Education Conference, EDUCON, pp. 374-383, 2019.
  • E. Philip – S. Golluri: Implementation of an Autonomous Self-Balancing Robot Using Cascaded PID Strategy. In 2020 6th International Conference on Control, Automation and Robotics (ICCAR), pp. 74-79, 2020.
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