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Contact:
Room: 522, https://telco.pcz.pl/and-d9x-drw

Position:
Associate Professor

Classes:
Systemy operacyjne czasu rzeczywistego lab.
Systemy operacyjne czasu rzeczywistego wyk.
Jed. oblicz. w zastosowaniach mechatroni. lab.
Jed. oblicz. w zastosowaniach mechatroni. wyk.
PhD DSc Eng Andrzej Przybył
Office hours: wtorki 15.15-16.45

Papers (40)

2021 (1)

Fixed-Point Arithmetic Unit with a Scaling Mechanism for FPGA-Based Embedded Systems
Andrzej Przybył, Fixed-Point Arithmetic Unit with a Scaling Mechanism for FPGA-Based Embedded Systems, Multidisciplinary Digital Publishing Institute, 1164, 2021, Cites: 0

2018 (3)

Genetic programming algorithm for designing of control systems
Krzysztof Cpalka and Krystian Łapa and Andrzej Przybył, Genetic programming algorithm for designing of control systems, 668-683, 2018, Cites: 10
Hard real-time communication solution for mechatronic systems
A. Przybył, Hard real-time communication solution for mechatronic systems, Elsevier Ltd., 309-316, 2018, Cites: 6
Negative space-based population initialization algorithm (NSPIA)
Krystian Łapa and Krzysztof Cpałka and Andrzej Przybył and Konrad Grzanek, Negative space-based population initialization algorithm (NSPIA), Springer, Cham, 449-461, 2018, Cites: 8

2017 (2)

A Method for Design of Hardware Emulators for a Distributed Network Environment
Andrzej Przybył and Meng Joo Er, A Method for Design of Hardware Emulators for a Distributed Network Environment, Springer, Cham, 318-336, 2017, Cites: 1
Fuzzy PID controllers with FIR filtering and a method for their construction
Krystian Łapa and Krzysztof Cpałka and Andrzej Przybył and Takamichi Saito, Fuzzy PID controllers with FIR filtering and a method for their construction, Springer, Cham, 292-307, 2017, Cites: 4

2016 (5)

A new approach to nonlinear modelling of dynamic systems based on fuzzy rules
Łukasz Bartczuk and Andrzej Przybył and Krzysztof Cpałka, A new approach to nonlinear modelling of dynamic systems based on fuzzy rules, 2016, Cites: 30
The method of the evolutionary designing the elastic controller structure
Andrzej Przybył and Krystian Łapa and Jacek Szczypta and Lipo Wang, The method of the evolutionary designing the elastic controller structure, Springer, Cham, 476-492, 2016, Cites: 3
A new approach to designing of intelligent emulators working in a distributed environment
Andrzej Przybył and Meng Joo Er, A new approach to designing of intelligent emulators working in a distributed environment, Springer, Cham, 546-558, 2016, Cites: 6
Method of evolutionary designing of FPGA-based controllers
Andrzej Przybył and Jacek Szczypta, Method of evolutionary designing of FPGA-based controllers, 174-179, 2016, Cites: 4
The method of hardware implementation of fuzzy systems on FPGA
Andrzej Przybył and Meng Joo Er, The method of hardware implementation of fuzzy systems on FPGA, Springer, Cham, 284-298, 2016, Cites: 12

2015 (3)

A new approach to design of control systems using genetic programming
Krzysztof Cpalka and Krystian Łapa and Andrzej Przybył, A new approach to design of control systems using genetic programming, 433-442, 2015, Cites: 43
New method for non-linear correction modelling of dynamic objects with genetic programming
Łukasz Bartczuk and Andrzej Przybył and Petia Koprinkova-Hristova, New method for non-linear correction modelling of dynamic objects with genetic programming, Springer, Cham, 318-329, 2015, Cites: 8
Optimization of controller structure using evolutionary algorithm
Andrzej Przybył and Jacek Szczypta and Lipo Wang, Optimization of controller structure using evolutionary algorithm, Springer, Cham, 261-271, 2015, Cites: 3

2014 (5)

A new algorithm for identification of significant operating points using swarm intelligence
Piotr Dziwiński and Łukasz Bartczuk and Andrzej Przybył and Eduard D Avedyan, A new algorithm for identification of significant operating points using swarm intelligence, Springer, Cham, 349-362, 2014, Cites: 32
Evolutionary approach with multiple quality criteria for controller design
Jacek Szczypta and Andrzej Przybył and Lipo Wang, Evolutionary approach with multiple quality criteria for controller design, Springer, Cham, 455-467, 2014, Cites: 12
A new method for designing neuro-fuzzy systems for nonlinear modelling with interpretability aspects
K Cpałka and K Łapa and A Przybył and M Zalasiński, A new method for designing neuro-fuzzy systems for nonlinear modelling with interpretability aspects, Elsevier, 203-217, 2014, Cites: 70
New method for nonlinear fuzzy correction modelling of dynamic objects
Łukasz Bartczuk and Andrzej Przybył and Petia Koprinkova-Hristova, New method for nonlinear fuzzy correction modelling of dynamic objects, Springer, Cham, 169-180, 2014, Cites: 25
The idea for the integration of neuro-fuzzy hardware emulators with real-time network
Andrzej Przybył and Meng Joo Er, The idea for the integration of neuro-fuzzy hardware emulators with real-time network, Springer, Cham, 279-294, 2014, Cites: 12

2013 (3)

Some aspects of evolutionary designing optimal controllers
Jacek Szczypta and Andrzej Przybył and Krzysztof Cpałka, Some aspects of evolutionary designing optimal controllers, Springer, Berlin, Heidelberg, 91-100, 2013, Cites: 28
A new approach to designing interpretable models of dynamic systems
Krystian Łapa and Andrzej Przybył and Krzysztof Cpałka, A new approach to designing interpretable models of dynamic systems, Springer, Berlin, Heidelberg, 523-534, 2013, Cites: 44
Hybrid state variables-fuzzy logic modelling of nonlinear objects
Łukasz Bartczuk and Andrzej Przybył and Piotr Dziwiński, Hybrid state variables-fuzzy logic modelling of nonlinear objects, Springer, Berlin, Heidelberg, 227-234, 2013, Cites: 19

2012 (2)

A new method to construct of interpretable models of dynamic systems
Andrzej Przybył and Krzysztof Cpałka, A new method to construct of interpretable models of dynamic systems, Springer, Berlin, Heidelberg, 697-705, 2012, Cites: 43
Novel on-line speed profile generation for industrial machine tool based on flexible neuro-fuzzy approximation
Krzysztof Cpałka Leszek Rutkowski and Andrzej Przybył, Novel on-line speed profile generation for industrial machine tool based on flexible neuro-fuzzy approximation, 1238-1247, 2012, Cites: 93

2010 (3)

Real-time Ethernet based, distributed control system for the CNC machine
A Przybył and J Smoląg and P Kimla, Real-time Ethernet based, distributed control system for the CNC machine, 2010, Cites: 5
Online speed profile generation for industrial machine tool based on neuro-fuzzy approach
Leszek Rutkowski and Andrzej Przybył and Krzysztof Cpałka and Meng Joo Er, Online speed profile generation for industrial machine tool based on neuro-fuzzy approach, Springer, Berlin, Heidelberg, 645-650, 2010, Cites: 53
Rozproszony system sterowania obrabiarką numeryczną bazujący na sieci Ethernet Czasu Rzeczywistego
A Przybył and J Smoląg and P Kimla, Rozproszony system sterowania obrabiarką numeryczną bazujący na sieci Ethernet Czasu Rzeczywistego, 342-346, 2010, Cites: 0

2009 (2)

Rozproszony system sterowania obrabiarką numeryczną bazujący na sieci Ethernet Czasu Rzeczywistego.
Andrzej Przybył Jacek Smoląg and Przemysław Kimla, Rozproszony system sterowania obrabiarką numeryczną bazujący na sieci Ethernet Czasu Rzeczywistego., 2009, Cites: 0
Realizacja w układzie FPGA algorytmu pomiaru prędkości, bazującego na kompensowanym enkoderze inkrementalnym
Andrzej Przybył, Realizacja w układzie FPGA algorytmu pomiaru prędkości, bazującego na kompensowanym enkoderze inkrementalnym, 2009, Cites: 0

2008 (1)

Accuracy improvement of neural network state variable estimator in induction motor drive
Jerzy Jelonkiewicz and Andrzej Przybył, Accuracy improvement of neural network state variable estimator in induction motor drive, Springer, Berlin, Heidelberg, 71-77, 2008, Cites: 6

2005 (1)

Knowledge extraction from data for neural network state variables estimators in induction motor
Jerzy Jelonkiewicz Andrzej Przybył, Knowledge extraction from data for neural network state variables estimators in induction motor, 211–216, 2005, Cites: 2

2004 (2)

Influence of the training set selection on the performance of the neural network state variables estimators in the induction motor
Jerzy Jelonkiewicz and Andrzej Przybył, Influence of the training set selection on the performance of the neural network state variables estimators in the induction motor, Springer, Berlin, Heidelberg, 966-971, 2004, Cites: 0
State Feedback-Based Control of an Induction Motor in a Single Fixed-Point DSP
Andrzej Przybył Jerzy Jelonkiewicz, State Feedback-Based Control of an Induction Motor in a Single Fixed-Point DSP, 1-8, CD, 2004, Cites: 1

2003 (2)

Ewolucja czy rewolucja.Nowoczesne techniki informatyczne.
Jerzy Jelonkiewicz Andrzej Przybył, Ewolucja czy rewolucja.Nowoczesne techniki informatyczne., Katedra Inżynierii Komputerowej Politechniki Czest, 493-496, 2003, Cites: 0
Genetic Algorithm for Observer Parameters Tuning in Sensorless Induction Motor Drive.
Andrzej Przybył Jerzy Jelonkiewicz, Genetic Algorithm for Observer Parameters Tuning in Sensorless Induction Motor Drive., 376-381, 2003, Cites: 20

2001 (2)

Neural Networks Implementation of Model Reference Adaptive Systems in Induction Motor Drive
Jerzy Jelonkiewicz Andrzej Przybył, Neural Networks Implementation of Model Reference Adaptive Systems in Induction Motor Drive, CD, 2001, Cites: 0
Induction Motor Parameters Identification Based On Genetic Algorithm
Andrzej Przybył Jerzy Jelonkiewicz, Induction Motor Parameters Identification Based On Genetic Algorithm, 501-506, 2001, Cites: 5

1999 (2)

Fuzzy-neural networks in efficiency optimal control of induction motor
Jerzy Jelonkiewicz Andrzej Przybył, Fuzzy-neural networks in efficiency optimal control of induction motor, 1999, Cites: 0
Efficiency optimal control method of induction motor drive for light vehicles
Jerzy Jelonkiewicz Andrzej Przybył, Efficiency optimal control method of induction motor drive for light vehicles, 1999, Cites: 0

1998 (1)

High Efficient Induction Motor Drive for Light Vehicle
Jerzy Jelonkiewicz Andrzej Przybył, High Efficient Induction Motor Drive for Light Vehicle, 1998, Cites: 0

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