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Contact:
Room: 522

Position:
Associate Professor

Classes:
Systemy wbudowane wyk
Systemy wbudowane w układach sterowania wyk
Programowanie systemów wbudowanych wyk
PhD DSc Eng Andrzej Przybył
Office hours: Wtorki 12.30-14.00 w sali 522 w KISI lub w trybie on-line po wcześniejszym uzgodnieniu. Możliwy jest dodatkowy termin konsultacji w niedzielę 03.12.2023 w godz. 10.30-12.00 po wcześniejszym indywidualnym e-mailowym uzgodnieniu.

Papers (30)

2023 (1)

FPGA-Based Optimization of Industrial Numerical Machine Tool Servo Drives
Przybyl A., FPGA-Based Optimization of Industrial Numerical Machine Tool Servo Drives, Electronics (Switzerland), 12, 12, 2023, Cites: 0

2021 (2)

Hardware implementation of a Takagi-Sugeno neuro-fuzzy system optimized by a population algorithm
Dziwinski P., Przybyl A., Trippner P., Paszkowski J., Hayashi Y., Hardware implementation of a Takagi-Sugeno neuro-fuzzy system optimized by a population algorithm, Journal of Artificial Intelligence and Soft Computing Research, 11, 11, 243-266, 2021, Cites: 10
Fixed-point arithmetic unit with a scaling mechanism for fpga-based embedded systems
Przybyl A., Fixed-point arithmetic unit with a scaling mechanism for fpga-based embedded systems, Electronics (Switzerland), 10, 10, 2021, Cites: 6

2018 (3)

Negative space-based population initialization algorithm (NSPIA)
Lapa K., Cpalka K., Przybyl A., Grzanek K., Negative space-based population initialization algorithm (NSPIA), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 10841 LNAI, 10841 LNAI, 449-461, 2018, Cites: 8
Genetic programming algorithm for designing of control systems
Lapa K., Cpalka K., Przybyl A., Genetic programming algorithm for designing of control systems, Information Technology and Control, 47, 47, 668-683, 2018, Cites: 16
Hard real-time communication solution for mechatronic systems
Przybyl A., Hard real-time communication solution for mechatronic systems, Robotics and Computer-Integrated Manufacturing, 49, 49, 309-316, 2018, Cites: 6

2017 (2)

A method for design of hardware emulators for a distributed network environment
Przybyl A., Er M.J., A method for design of hardware emulators for a distributed network environment, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 10246 LNAI, 10246 LNAI, 318-336, 2017, Cites: 1
Fuzzy PID controllers with FIR filtering and a method for their construction
Lapa K., Cpalka K., Przybyl A., Saito T., Fuzzy PID controllers with FIR filtering and a method for their construction, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 10246 LNAI, 10246 LNAI, 292-307, 2017, Cites: 4

2016 (5)

The method of hardware implementation of fuzzy systems on FPGA
Przybyl A., Joo Er M., The method of hardware implementation of fuzzy systems on FPGA, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 9692, 9692, 284-298, 2016, Cites: 9
A new approach to designing of intelligent emulators working in a distributed environment
Przybyl A., Er M.J., A new approach to designing of intelligent emulators working in a distributed environment, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 9693, 9693, 546-558, 2016, Cites: 4
Method of evolutionary designing of FPGA-based controllers
Przybyl A., Szczypta J., Method of evolutionary designing of FPGA-based controllers, Przeglad Elektrotechniczny, 92, 92, 174-179, 2016, Cites: 5
A new approach to nonlinear modelling of dynamic systems based on fuzzy rules
Bartczuk L., Przybyl A., Cpalka K., A new approach to nonlinear modelling of dynamic systems based on fuzzy rules, International Journal of Applied Mathematics and Computer Science, 26, 26, 603-621, 2016, Cites: 35
The method of the evolutionary designing the elastic controller structure
Przybyl A., Lapa K., Szczypta J., Wang L., The method of the evolutionary designing the elastic controller structure, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 9692, 9692, 476-492, 2016, Cites: 3

2015 (3)

Optimization of controller structure using evolutionary algorithm
Przybyl A., Szczypta J., Wang L., Optimization of controller structure using evolutionary algorithm, Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science), 9120, 9120, 261-271, 2015, Cites: 2
A new approach to design of control systems using genetic programming
Cpalka K., Lapa K., Przybyl A., A new approach to design of control systems using genetic programming, Information Technology and Control, 44, 44, 433-442, 2015, Cites: 40
New method for non-linear correction modelling of dynamic objects with genetic programming
Bartczuk L., Przybyl A., Koprinkova-Hristova P., New method for non-linear correction modelling of dynamic objects with genetic programming, Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science), 9120, 9120, 318-329, 2015, Cites: 9

2014 (5)

A new method for designing neuro-fuzzy systems for nonlinear modelling with interpretability aspects
Cpalka K., Lapa K., Przybyl A., Zalasinski M., A new method for designing neuro-fuzzy systems for nonlinear modelling with interpretability aspects, Neurocomputing, 135, 135, 203-217, 2014, Cites: 80
New method for nonlinear fuzzy correction modelling of dynamic objects
Bartczuk L., Przybyl A., Koprinkova-Hristova P., New method for nonlinear fuzzy correction modelling of dynamic objects, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 8467 LNAI, 8467 LNAI, 169-180, 2014, Cites: 26
A new algorithm for identification of significant operating points using swarm intelligence
Dziwinski P., Bartczuk L., Przybyl A., Avedyan E.D., A new algorithm for identification of significant operating points using swarm intelligence, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 8468 LNAI, 8468 LNAI, 349-362, 2014, Cites: 32
The idea for the integration of neuro-fuzzy hardware emulators with real-time network
Przybyl A., Er M.J., The idea for the integration of neuro-fuzzy hardware emulators with real-time network, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 8467 LNAI, 8467 LNAI, 279-294, 2014, Cites: 12
Evolutionary approach with multiple quality criteria for controller design
Szczypta J., Przybyl A., Wang L., Evolutionary approach with multiple quality criteria for controller design, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 8467 LNAI, 8467 LNAI, 455-467, 2014, Cites: 12

2013 (3)

Hybrid state variables - Fuzzy logic modelling of nonlinear objects
Bartczuk L., Przybyl A., Dziwinski P., Hybrid state variables - Fuzzy logic modelling of nonlinear objects, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 7894 LNAI, 7894 LNAI, 227-234, 2013, Cites: 19
Some aspects of evolutionary designing optimal controllers
Szczypta J., Przybyl A., Cpalka K., Some aspects of evolutionary designing optimal controllers, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 7895 LNAI, 7895 LNAI, 91-100, 2013, Cites: 35
A new approach to designing interpretable models of dynamic systems
Lapa K., Przybyl A., Cpalka K., A new approach to designing interpretable models of dynamic systems, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 7895 LNAI, 7895 LNAI, 523-534, 2013, Cites: 45

2012 (2)

A new method to construct of interpretable models of dynamic systems
Przybyl A., Cpalka K., A new method to construct of interpretable models of dynamic systems, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 7268 LNAI, 7268 LNAI, 697-705, 2012, Cites: 43
Novel online speed profile generation for industrial machine tool based on flexible neuro-fuzzy approximation
Rutkowski L., Przybyl A., Cpalka K., Novel online speed profile generation for industrial machine tool based on flexible neuro-fuzzy approximation, IEEE Transactions on Industrial Electronics, 59, 59, 1238-1247, 2012, Cites: 89

2010 (2)

Distributed control system based on real time ethernet for computer numerical controlled machine tool
PrzybyL A., Smolag J., Kimla P., Distributed control system based on real time ethernet for computer numerical controlled machine tool, Przeglad Elektrotechniczny, 86, 86, 342-346, 2010, Cites: 16
Online speed profile generation for industrial machine tool based on neuro-fuzzy approach
Rutkowski L., Przybyl A., Cpalka K., Er M.J., Online speed profile generation for industrial machine tool based on neuro-fuzzy approach, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 6114 LNAI, 6114 LNAI, 645-650, 2010, Cites: 53

2008 (1)

Accuracy improvement of neural network state variable estimator in induction motor drive
Jelonkiewicz J., Przybyl A., Accuracy improvement of neural network state variable estimator in induction motor drive, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 5097 LNAI, 5097 LNAI, 71-77, 2008, Cites: 5

2004 (1)

Influence of the training set selection on the performance of the neural network state variables estimators in the induction motor
Jelonkiewicz J., Przybyl A., Influence of the training set selection on the performance of the neural network state variables estimators in the induction motor, Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science), 3070, 3070, 966-971, 2004, Cites: 0

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