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Contact:
Room: 522
Position:
Associate Professor
Classes:
Programowanie systemów wbudowanych lab
Programowanie systemów wbudowanych wyk
PhD DSc Eng Prof. Andrzej Przybył
Office hours: Środa, godz. 11.30 - 13:30. Konsultacje w wakacje odbywają się tylko w pierwszej połowie lipca po wcześniejszym uzgodnieniu terminu (e-mail).

ORCID: https://orcid.org/0000-0002-8052-4415 

Najnowsze publikacje:

2026:

Pawel Poczekajlo, Ewa Deelman, Michela Taufer, Pawel Gepner, Leonid Moroz, Jerzy Krawiec, Andrzej Przybyl, Low-latency hybrid CORDIC framework on FPGAs, Journal of Computational Science, 2026.

Free access to the article for anyone clicking on this link before August 02, 2026. No sign up, registration or fees are required:

https://authors.elsevier.com/c/1nGLw6gytHA7zd

2023: 

FPGA-Based Optimization of Industrial Numerical Machine Tool Servo Drives:

2021: 

Hardware implementation of a Takagi-Sugeno neuro-fuzzy system optimized by a population algorithm

Fixed-Point Arithmetic Unit with a Scaling Mechanism for FPGA-Based Embedded Systems

 

Proponowane tematy prac dyplomowych na rok 2024

Studia I-go stopnia:

  1. Ethernet przemysłowy.
    1. Opis podstawowych informacji o tym, czym jest i do czego jest wykorzystywany Ethernet przemysłowy. Przegląd rozwiązań dostępnych na rynku.
    2. Implementacja oprogramowania dla komputera PC do komunikacji z robotem współpracującym UR5e w oparciu o wybrany protokół: ModbusTCP, ProfiNet (jeśli znajdą się darmowe rozwiązania) lub EthernetIP.

       

  2. Magistrala komunikacyjna CAN.
    1. Opis budowy i właściwości magistrali CAN.
    2. Implementacja oprogramowania dla mikrokontrolera ARM Cortex-M4 do komunikacji z innymi urządzeniami w oparciu o magistralę CAN.
    3. Zaprojektowanie na sterownikach PLC-HMI (model US7 B10-TA30 Unistream firmy Unitronics) modeli demonstracyjnych kilku prostych obiektów przemysłowych. Modele te będą wykorzystywane do współpracy z oprogramowaniem mikrokontrolera. https://www.unitronicsplc.pl/4566-us7-b10-TA30-panel-graficzny-hmi-przekatna-7-cali.html
    4. Sterowanie za pośrednictwem magistrali CAN gotowym modułem z silnikiem krokowym.
    5. Zaprojektowanie interfejsu graficznego wyświetlanego na panelu LCD głównego sterownika.
    6. Wykonanie pomiarów ruchu w sieci CAN za pomocą analizatora sieciowego.

  3. Modelowanie pracy obiektów przemysłowych na platformach PLC-HMI.
    1. Krótki opis podstawowych metod modelowania obiektów dynamicznych w oparciu o równania różniczkowe.
    2. Wykonanie oprogramowania w środowisku UniLogic dla sterowników PLC-HMI (model US5 B10-TA30 Unistream firmy Unitronics) symulującego działanie kilku prostych obiektów przemysłowych. Oprogramowanie będzie wykonane w języku drabinkowym z wstawkami w języku C. https://www.elmark.com.pl/blog/akademia-plc-elmark-unitronics-unistream 
    3. Zaprojektowanie współpracy za pośrednictwem interfejsu analogowego i cyfrowego z innymi sterownikami, w tym z mikrokontrolerami.

       

  4. Interfejsy komunikacyjne OPC-UA i MQTT.
    1. Projekt i implementacja oprogramowania dla mikrokontrolerów ARM Cortex-M4 komunikującego się za pomocą w/w protokołów.
    2. Projekt i implementacja adekwatnego oprogramowania dla komputera PC.

 

Studia II-go stopnia:

  1. Metody numeryczne w zagadnieniach aproksymacji funkcji nieliniowych w systemach wbudowanych / Aproksymacja funkcji nieliniowych do zastosowań w systemach wbudowanych.
    1. Zaprojektowanie i implementacja oprogramowania dla MCU lub FPGA.
    2. Wykonanie testów, opracowanie wyników.

Papers (31)

2026 (1)

Low-latency hybrid CORDIC framework on FPGAs
Poczekajlo P., Deelman E., Taufer M., Gepner P., Moroz L., Krawiec J., Przybyl A., Low-latency hybrid CORDIC framework on FPGAs, Journal of Computational Science, 99, 99, 2026, Cites: 0

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: 5

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: 13
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: 15

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
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: 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: 19

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: 5

2016 (5)

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
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: 10
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: 38
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 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

2015 (3)

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
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
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: 3

2014 (5)

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
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: 34
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
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
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: 82

2013 (3)

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: 46
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: 36

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: 91

2010 (2)

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: 54
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

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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