LSTM and GRU neural networks as models of dynamical processes used in predictive control: A comparison of models developed for two chemical reactors K Zarzycki, M Ławryńczuk Sensors 21 (16), 5625, 2021 | 98 | 2021 |
Advanced predictive control for GRU and LSTM networks K Zarzycki, M Ławryńczuk Information Sciences 616, 229-254, 2022 | 87 | 2022 |
Fast real-time model predictive control for a ball-on-plate process K Zarzycki, M Ławryńczuk Sensors 21 (12), 3959, 2021 | 19 | 2021 |
Predictive tracking of an object by a pan–tilt camera of a robot R Nebeluk, K Zarzycki, D Seredyński, P Chaber, M Figat, PD Domański, ... Nonlinear Dynamics 111 (9), 8383-8395, 2023 | 7 | 2023 |
Forgery Cyber-Attack Supported by LSTM Neural Network: An Experimental Case Study K Zarzycki, P Chaber, K Cabaj, M Ławryńczuk, P Marusak, R Nebeluk, ... Sensors 23 (15), 6778, 2023 | 6 | 2023 |
Digital Twins in the Practice of High-Energy Physics Experiments: A Gas System for the Multipurpose Detector P Chaber, PD Domański, D Dąbrowski, M Ławryńczuk, R Nebeluk, ... Sensors 22 (2), 678, 2022 | 5 | 2022 |
GAN Neural Networks Architectures for Testing Process Control Industrial Network Against Cyber-Attacks K Zarzycki, P Chaber, K Cabaj, M Ławryńczuk, P Marusak, R Nebeluk, ... IEEE Access 11, 49587-49600, 2023 | 4 | 2023 |
LSTM for Modelling and Predictive Control of Multivariable Processes K Zarzycki, M Ławryńczuk International Conference on Innovative Techniques and Applications of …, 2024 | 2 | 2024 |
Long Short-Term Memory Neural Networks for Modeling Dynamical Processes and Predictive Control: A Hybrid Physics-Informed Approach K Zarzycki, M Ławryńczuk Sensors 23 (21), 8898, 2023 | 2 | 2023 |
Practical Digital Twins Application to High Energy Systems: Thermal Protection for Multi-Detector A Wojtulewicz, PD Domański, M Czarnynoga, M Kutyła, M Ławryńczuk, ... Electronics 11 (14), 2269, 2022 | 2 | 2022 |
Fast Nonlinear Model Predictive Control Using LSTM Networks: A Model Linearisation Approach K Zarzycki, M Ławryńczuk 2022 30th Mediterranean Conference on Control and Automation (MED), 1-6, 2022 | 2 | 2022 |
Development and modelling of a laboratory ball on plate process K Zarzycki, M Ławryńczuk Advanced, Contemporary Control: Proceedings of KKA 2020—The 20th Polish …, 2020 | 2 | 2020 |
Methodology for Conducting a Study of the Vulnerability of PLC Control Algorithms to Cyber Attacks S Plamowski, R Nebeluk, A Wojtulewicz, K Cabaj, P Chaber, ... IEEE Access, 2024 | 1 | 2024 |
Efficient Cyberattack Detection Methods in Industrial Control Systems P Marusak, R Nebeluk, A Wojtulewicz, K Cabaj, P Chaber, M Ławryńczuk, ... Sensors 24 (12), 3860, 2024 | 1 | 2024 |
Physics-Informed Hybrid Neural Network Model for MPC: A Fuzzy Approach K Zarzycki, M Ławryńczuk Proceedings of the XXI Polish Control Conference, 183-192, 2023 | 1 | 2023 |
Physics-Informed Hybrid GRU Neural Networks for MPC Prediction K Zarzycki, M Lawryńczuk IFAC-PapersOnLine 56 (2), 8726-8731, 2023 | 1 | 2023 |
Infrastructure and Tools for Testing the Vulnerability of Control Systems to Cyberattacks: A Coal Mine Industrial Facility Case S Plamowski, P Chaber, M Ławryńczuk, R Nebeluk, ... Applied Sciences 14 (23), 11325, 2024 | | 2024 |
On the simplification of the internal nonlinear robot models for the MPC-based visual servoing P Chaber, PD Domański, PM Marusak, R Nebeluk, D Seredyński, ... Nonlinear Dynamics, 1-25, 2024 | | 2024 |
Metody sztucznej inteligencji do detekcji ataków na sieci OT P Chaber, M Ławryńczuk, R Nebeluk, S Plamowski, P Suchorab, ... Główny Instytut Górnictwa, 2024 | | 2024 |