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Maciej Lawrynczuk
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2020 – today
- 2024
- [j39]Sebastian Plamowski
, Robert Nebeluk
Methodology for Conducting a Study of the Vulnerability of PLC Control Algorithms to Cyber Attacks. IEEE Access 12: 135551-135563 (2024) - [j38]Piotr M. Marusak
Efficient Cyberattack Detection Methods in Industrial Control Systems. Sensors 24(12): 3860 (2024) - 2023
- [j37]Krzysztof Zarzycki
GAN Neural Networks Architectures for Testing Process Control Industrial Network Against Cyber-Attacks. IEEE Access 11: 49587-49600 (2023) - [j36]Krzysztof Zarzycki
Forgery Cyber-Attack Supported by LSTM Neural Network: An Experimental Case Study. Sensors 23(15): 6778 (2023) - [j35]Krzysztof Zarzycki
Long Short-Term Memory Neural Networks for Modeling Dynamical Processes and Predictive Control: A Hybrid Physics-Informed Approach. Sensors 23(21): 8898 (2023) - [j34]Robert Nebeluk
Fast Nonlinear Predictive Control Using Classical and Parallel Wiener Models: A Comparison for a Neutralization Reactor Process. Sensors 23(23): 9539 (2023) - [c59]Krzysztof Zarzycki, Maciej Lawrynczuk:
Physics-Informed Hybrid Neural Network Model for MPC: A Fuzzy Approach. PCC (1) 2023: 183-192 - [c58]Robert Nebeluk, Maciej Lawrynczuk:
On the Choice of the Cost Function for Nonlinear Model Predictive Control: A Multi-criteria Evaluation. PCC (1) 2023: 361-371 - 2022
- [b1]Maciej Lawrynczuk:
Nonlinear Predictive Control Using Wiener Models - Computationally Efficient Approaches for Polynomial and Neural Structures. Springer 2022, ISBN 978-3-030-83814-0, pp. 3-340 - [j33]Maciej Lawrynczuk
Special Issue "Model Predictive Control: Algorithms and Applications": Foreword by the Guest Editor. Algorithms 15(12): 452 (2022) - [j32]Maciej Lawrynczuk:
Input convex neural networks in nonlinear predictive control: A multi-model approach. Neurocomputing 513: 273-293 (2022) - [j31]Krzysztof Zarzycki, Maciej Lawrynczuk:
Advanced predictive control for GRU and LSTM networks. Inf. Sci. 616: 229-254 (2022) - [j30]Patryk Chaber
Digital Twins in the Practice of High-Energy Physics Experiments: A Gas System for the Multipurpose Detector. Sensors 22(2): 678 (2022) - [c57]Krzysztof Zarzycki, Maciej Lawrynczuk:
Fast Nonlinear Model Predictive Control Using LSTM Networks: A Model Linearisation Approach. MED 2022: 1-6 - [c56]Robert Nebeluk, Maciej Lawrynczuk:
Fast Nonlinear Model Predictive Control Using a Custom Cost-Function: Preliminary Results. MED 2022: 13-18 - 2021
- [j29]Michal Okulski
A Novel Neural Network Model Applied to Modeling of a Tandem-Wing Quadplane Drone. IEEE Access 9: 14159-14178 (2021) - [j28]Robert Nebeluk
Computationally Simple Nonlinear MPC Algorithm for Vehicle Obstacle Avoidance With Minimization of Fuel Utilization. IEEE Access 9: 17296-17311 (2021) - [j27]Pawel D. Domanski
Impact of MPC Embedded Performance Index on Control Quality. IEEE Access 9: 24787-24795 (2021) - [j26]Robert Nebeluk
Tuning of Multivariable Model Predictive Control for Industrial Tasks. Algorithms 14(1): 10 (2021) - [j25]Inez Okulska
Make a difference, open the door: The energy-efficient multi-layer thermal comfort control system based on a graph airflow model with doors and windows. Inf. Sci. 579: 553-573 (2021) - [j24]Krzysztof Zarzycki
Fast Real-Time Model Predictive Control for a Ball-on-Plate Process. Sensors 21(12): 3959 (2021) - [j23]Krzysztof Zarzycki
LSTM and GRU Neural Networks as Models of Dynamical Processes Used in Predictive Control: A Comparison of Models Developed for Two Chemical Reactors. Sensors 21(16): 5625 (2021) - [j22]Maciej Lawrynczuk
Computationally Efficient Nonlinear Model Predictive Control Using the L1 Cost-Function. Sensors 21(17): 5835 (2021) - 2020
- [j21]Pawel D. Domanski
Control Quality Assessment for Processes With Asymmetric Properties and its Application to pH Reactor. IEEE Access 8: 94535-94546 (2020) - [j20]Krzysztof Dziuba
Multicriteria Ammonia Plant Assessment for the Advanced Process Control Implementation. IEEE Access 8: 207923-207937 (2020) - [j19]Maciej Lawrynczuk:
Nonlinear Model Predictive Control for Processes with Complex Dynamics: A Parameterisation Approach Using Laguerre Functions. Int. J. Appl. Math. Comput. Sci. 30(1): 35-46 (2020) - [j18]Piotr Tatjewski
Algorithms with state estimation in linear and nonlinear model predictive control. Comput. Chem. Eng. 143: 107065 (2020) - [j17]Maciej Lawrynczuk
Offset-free state-space nonlinear predictive control for Wiener systems. Inf. Sci. 511: 127-151 (2020) - [j16]Patryk Chaber
AutoMATiC: Code Generation of Model Predictive Control Algorithms for Microcontrollers. IEEE Trans. Ind. Informatics 16(7): 4547-4556 (2020) - [c55]Pawel D. Domanski, Maciej Lawrynczuk:
Multi-Criteria Control Performance Assessment Method for Multivariate MPC. ACC 2020: 1968-1973 - [c54]Michal Okulski, Maciej Lawrynczuk:
Identification of Linear Models of a Tandem-Wing Quadplane Drone: Preliminary Results. KKA 2020: 219-228 - [c53]Andrzej Wojtulewicz
A System for Detection of Pressure Leaks. KKA 2020: 319-331 - [c52]Krzysztof Zarzycki
Development and Modelling of a Laboratory Ball on Plate Process. KKA 2020: 396-408 - [c51]Robert Nebeluk
Tuning of Nonlinear MPC Algorithm for Vehicle Obstacle Avoidance. KKA 2020: 993-1005 - [c50]Jakub Sawulski
PC-Based Simulation Environment for the Engine Control Optimiser Hardware-in-the-Loop Testing. KKA 2020: 1297-1308
2010 – 2019
- 2019
- [j15]Jakub Sawulski
Optimization of control strategy for a low fuel consumption vehicle engine. Inf. Sci. 493: 192-216 (2019) - [j14]Patryk Chaber
Fast Analytical Model Predictive Controllers and Their Implementation for STM32 ARM Microcontroller. IEEE Trans. Ind. Informatics 15(8): 4580-4590 (2019) - [c49]Jakub Sawulski
Real-Time Optimisation of Control Strategy for a Low Fuel Consumption Vehicle Engine Using STM32 Microcontroller: Preliminary Results. ECC 2019: 4246-4251 - [c48]Pawel D. Domanski, Maciej Lawrynczuk, Sebastian Golonka, Bartosz Moszowski, Piotr Matyja:
Multi-criteria Loop Quality Assessment: A Large-Scale Industrial Case Study. MMAR 2019: 99-104 - [c47]Michal Okulski, Maciej Lawrynczuk:
Development of a High-Efficiency Pitch/Roll Inertial Measurement Unit Based on a Low-Cost Accelerometer and Gyroscope Sensors. MMAR 2019: 657-662 - 2018
- [j13]Maciej Lawrynczuk
Towards Reduced-Order Models of Solid Oxide Fuel Cell. Complex. 2018: 6021249:1-6021249:18 (2018) - [c46]Michal Okulski, Maciej Lawrynczuk
A Cascade PD Controller for Heavy Self-balancing Robot. AUTOMATION 2018: 183-192 - [c45]Jakub Sawulski
Optimisation-Based Tuning of Dynamic Matrix Control Algorithm for Multiple-Input Multiple-Output Processes. MMAR 2018: 160-165 - [c44]Michal Okulski, Maciej Lawrynczuk
Development of a Model Predictive Controller for an Unstable Heavy Self-Balancing Robot. MMAR 2018: 503-508 - [c43]Andrzej Wojtulewicz
Computationally Efficient Implementation of Dynamic Matrix Control Algorithm for Very Fast Processes Using Programmable Logic Controller. MMAR 2018: 579-584 - 2017
- [j12]Pawel D. Domanski, Maciej Lawrynczuk
Assessment of the GPC Control Quality Using Non-Gaussian Statistical Measures. Int. J. Appl. Math. Comput. Sci. 27(2): 291 (2017) - [c42]Patryk Chaber
Automatic Code Generation of MIMO Model Predictive Control Algorithms using Transcompiler. KKA 2017: 315-324 - [c41]Patryk Chaber
Implementation of Analytical Generalized Predictive Controller for Very Fast Applications Using Microcontrollers: Preliminary Results. KKA 2017: 378-387 - [c40]Kamil Czerwinski, Maciej Lawrynczuk
Identification of Discrete-Time Model of Active Magnetic Levitation System. KKA 2017: 599-608 - 2016
- [j11]Maciej Lawrynczuk
Modelling and predictive control of a neutralisation reactor using sparse support vector machine Wiener models. Neurocomputing 205: 311-328 (2016) - [c39]Maciej Lawrynczuk
Neural Modelling of a Yeast Fermentation Process Using Extreme Learning Machines. AUTOMATION 2016: 13-23 - [c38]Antoni Wysocki, Maciej Lawrynczuk
Two- and Three-Layer Recurrent Elman Neural Networks as Models of Dynamic Processes. AUTOMATION 2016: 165-175 - [c37]Patryk Chaber
Auto-generation of advanced control algorithms' code for microcontrollers using transcompiler. MMAR 2016: 454-459 - [c36]Andrzej Wojtulewicz
Multiple-input multiple-output laboratory stand for process control education. MMAR 2016: 466-471 - [c35]Maciej Lawrynczuk
An easily trained neural model of a distributed parameter system. MMAR 2016: 674-679 - [c34]Piotr Tatjewski
Design and implementation of the air/water heat pump controller with increased coefficient of performance. MMAR 2016: 959-964 - 2015
- [j10]Maciej Lawrynczuk
Nonlinear State-Space Predictive Control With On-Line Linearisation And State Estimation. Int. J. Appl. Math. Comput. Sci. 25(4): 833-847 (2015) - [c33]Antoni Wysocki, Maciej Lawrynczuk
Jordan neural network for modelling and predictive control of dynamic systems. MMAR 2015: 145-150 - [c32]Maciej Lawrynczuk
Approximate state-space model predictive control. MMAR 2015: 770-775 - [c31]Patryk Chaber
RBF neural networks for modelling and predictive control: An application to a neutralisation process. MMAR 2015: 776-781 - [p4]Patryk Chaber
Recurrent Polynomial and Neural Structures in Modelling of a Neutralisation Process. Progress in Automation, Robotics and Measuring Techniques 2015: 23-32 - [p3]Antoni Wysocki, Maciej Lawrynczuk:
Predictive Control of a Multivariable Neutralisation Process Using Elman Neural Networks. Progress in Automation, Robotics and Measuring Techniques 2015: 335-344 - 2014
- [j9]Maciej Lawrynczuk
Explicit nonlinear predictive control algorithms with neural approximation. Neurocomputing 129: 570-584 (2014) - [c30]Maciej Lawrynczuk
Model predictive control with on-line optimal linearisation. ISIC 2014: 2177-2182 - [p2]Antoni Wysocki, Maciej Lawrynczuk
On Choice of the Sampling Period and the Horizons in Generalized Predictive Control. Recent Advances in Automation, Robotics and Measuring Techniques 2014: 329-339 - 2013
- [c29]Antoni Wysocki, Maciej Lawrynczuk:
An Investment Strategy for the Stock Exchange Using Neural Networks. FedCSIS 2013: 183-190 - [c28]Maciej Lawrynczuk
Development of Explicit Neural Predictive Control Algorithm Using Particle Swarm Optimisation. ICAISC (1) 2013: 130-139 - [c27]Maciej Lawrynczuk:
Nonlinear Predictive Control Based on Least Squares Support Vector Machines Hammerstein Models. ICANNGA 2013: 246-255 - 2012
- [c26]Maciej Lawrynczuk
On-Line Trajectory-Based Linearisation of Neural Models for a Computationally Efficient Predictive Control Algorithm. ICAISC (1) 2012: 126-134 - 2011
- [j8]Maciej Lawrynczuk
Accuracy and computational efficiency of suboptimal nonlinear predictive control based on neural models. Appl. Soft Comput. 11(2): 2202-2215 (2011) - [j7]Maciej Lawrynczuk
Online set-point optimisation cooperating with predictive control of a yeast fermentation process: A neural network approach. Eng. Appl. Artif. Intell. 24(6): 968-982 (2011) - [c25]Maciej Lawrynczuk
Nonlinear Predictive Control Based on Multivariable Neural Wiener Models. ICANNGA (1) 2011: 31-40 - [c24]Maciej Lawrynczuk
Predictive Control of a Distillation Column Using a Control-Oriented Neural Model. ICANNGA (1) 2011: 230-239 - [c23]Maciej Lawrynczuk
Precise and Computationally Efficient Nonlinear Predictive Control Based on Neural Wiener Models. ISMIS 2011: 663-672 - 2010
- [j6]Maciej Lawrynczuk
Nonlinear predictive control based on neural multi-models. Int. J. Appl. Math. Comput. Sci. 20(1): 7-21 (2010) - [j5]Maciej Lawrynczuk
Suboptimal nonlinear predictive control based on multivariable neural Hammerstein models. Appl. Intell. 32(2): 173-192 (2010) - [j4]Maciej Lawrynczuk
Training of neural models for predictive control. Neurocomputing 73(7-9): 1332-1343 (2010) - [j3]Maciej Lawrynczuk
Computationally efficient nonlinear predictive control based on neural Wiener models. Neurocomputing 74(1-3): 401-417 (2010) - [c22]Maciej Lawrynczuk
Dynamic Matrix Control Algorithm Based on Interpolated Step Response Neural Models. ICAISC (2) 2010: 297-304 - [c21]Maciej Lawrynczuk
Approximate Neural Economic Set-Point Optimisation for Control Systems. ICAISC (2) 2010: 305-312 - [c20]Maciej Lawrynczuk
Neural Dynamic Matrix Control Algorithm with Disturbance Compensation. IEA/AIE (3) 2010: 52-61 - [c19]Piotr Gawkowski
Testing Fault Robustness of Model Predictive Control Algorithms. ISARCS 2010: 109-124 - [c18]Maciej Lawrynczuk
Explicit Neural Network-Based Nonlinear Predictive Control with Low Computational Complexity. RSCTC 2010: 649-658
2000 – 2009
- 2009
- [j2]Maciej Lawrynczuk
Efficient Nonlinear Predictive Control Based on Structured Neural Models. Int. J. Appl. Math. Comput. Sci. 19(2): 233-246 (2009) - [c17]Piotr Gawkowski
On improving dependability of the numerical GPC algorithm. ECC 2009: 1377-1382 - [c16]Piotr Tatjewski
Integrated predictive optimiser and constraint supervisor for processes with basic feedback control. ECC 2009: 3359-3364 - [c15]Maciej Lawrynczuk
A Predictive Control Economic Optimiser and Constraint Governor Based on Neural Models. ICANNGA 2009: 79-88 - [c14]Maciej Lawrynczuk
Computationally Efficient Nonlinear Predictive Control Based on RBF Neural Multi-models. ICANNGA 2009: 89-98 - [c13]Maciej Lawrynczuk
Computationally Efficient Nonlinear Predictive Control Based on State-Space Neural Models. PPAM (1) 2009: 350-359 - [p1]Maciej Lawrynczuk
Neural Networks in Model Predictive Control. Intelligent Systems for Knowledge Management 2009: 31-63 - 2008
- [c12]Maciej Lawrynczuk
Optimising Predictive Control Based on Neural Models. AIMSA 2008: 118-129 - [c11]Maciej Lawrynczuk
Suboptimal Nonlinear Predictive Control Based on Neural Wiener Models. AIMSA 2008: 410-414 - [c10]Piotr Gawkowski
Dependability Comparison of Explicit and Numerical GPC Algorithms. EIAT/IETA 2008: 419-424 - [c9]Maciej Lawrynczuk
Efficient Predictive Control Algorithms Based on Soft Computing Approaches: Application to Glucose Concentration Stabilization. EIAT/IETA 2008: 425-430 - [c8]Maciej Lawrynczuk
Efficient Predictive Control Integrated with Economic Optimisation Based on Neural Models. ICAISC 2008: 111-122 - [c7]Maciej Lawrynczuk
Suboptimal Nonlinear Predictive Control with MIMO Neural Hammerstein Models. IEA/AIE 2008: 225-234 - 2007
- [j1]Maciej Lawrynczuk
A Family of Model Predictive Control Algorithms With Artificial Neural Networks. Int. J. Appl. Math. Comput. Sci. 17(2): 217-232 (2007) - [c6]Maciej Lawrynczuk:
Suboptimal Nonlinear Predictive Control with Structured Neural Models. ICANN (2) 2007: 630-639 - [c5]Maciej Lawrynczuk:
Neural Models in Computationally Efficient Predictive Control Cooperating with Economic Optimisation. ICANN (2) 2007: 650-659 - [c4]Maciej Lawrynczuk:
Jet Engine Turbine and Compressor Characteristics Approximation by Means of Artificial Neural Networks. ICANNGA (2) 2007: 143-152 - [c3]Maciej Lawrynczuk, Piotr Tatjewski:
A Computationally Efficient Nonlinear Predictive Control Algorithm with RBF Neural Models and Its Application. RSEISP 2007: 603-612 - 2006
- [c2]Maciej Lawrynczuk, Piotr Tatjewski:
An Efficient Nonlinear Predictive Control Algorithm with Neural Models and Its Application to a High-Purity Distillation Process. ICAISC 2006: 76-85 - 2003
- [c1]Maciej Lawrynczuk, Piotr Tatjewski:
An iterative nonlinear predictive control algorithm based on linearisation and neural models. ECC 2003: 1996-2001
Coauthor Index
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last updated on 2024-10-23 20:32 CEST by the dblp team
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