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Andrzej Przybył
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Novel on-line speed profile generation for industrial machine tool based on flexible neuro-fuzzy approximation
KC Leszek Rutkowski, Andrzej Przybył
IEEE Transactions on Industrial Electronics 59 (2), 1238-1247, 2012
100*2012
A new method for designing neuro-fuzzy systems for nonlinear modelling with interpretability aspects
K Cpałka, K Łapa, A Przybył, M Zalasiński
Neurocomputing 135, 203-217, 2014
822014
Online speed profile generation for industrial machine tool based on neuro-fuzzy approach
L Rutkowski, A Przybył, K Cpałka, MJ Er
International Conference on Artificial Intelligence and Soft Computing, 645-650, 2010
552010
A new approach to nonlinear modelling of dynamic systems based on fuzzy rules
Ł Bartczuk, A Przybył, K Cpałka
International Journal of Applied Mathematics and Computer Science 26 (3), 2016
502016
A new approach to designing interpretable models of dynamic systems
K Łapa, A Przybył, K Cpałka
International Conference on Artificial Intelligence and Soft Computing, 523-534, 2013
472013
A new approach to design of control systems using genetic programming
K Cpalka, K Łapa, A Przybył
Information technology and control 44 (4), 433-442, 2015
462015
Some aspects of evolutionary designing optimal controllers
J Szczypta, A Przybył, K Cpałka
International Conference on Artificial Intelligence and Soft Computing, 91-100, 2013
452013
A new method to construct of interpretable models of dynamic systems
A Przybył, K Cpałka
Artificial Intelligence and Soft Computing: 11th International Conference …, 2012
432012
A new algorithm for identification of significant operating points using swarm intelligence
P Dziwiński, Ł Bartczuk, A Przybył, ED Avedyan
Artificial Intelligence and Soft Computing: 13th International Conference …, 2014
322014
New method for nonlinear fuzzy correction modelling of dynamic objects
Ł Bartczuk, A Przybył, P Koprinkova-Hristova
Artificial Intelligence and Soft Computing: 13th International Conference …, 2014
262014
Genetic Algorithm for Observer Parameters Tuning in Sensorless Induction Motor Drive.
AP Jerzy Jelonkiewicz
Neural Networks and Soft Computing. Proceedings of the Sixth International …, 2003
21*2003
Genetic programming algorithm for designing of control systems
K Cpalka, K Łapa, A Przybył
Information Technology and Control 47 (4), 668-683, 2018
192018
Hybrid state variables-fuzzy logic modelling of nonlinear objects
Ł Bartczuk, A Przybył, P Dziwiński
Artificial Intelligence and Soft Computing: 12th International Conference …, 2013
192013
Distributed control system based on real time ethernet for computer numerical controlled machine tool
A Przybyl, J Smolag, P Kimla
Przeglad Elektrotechniczny 86 (2), 342-346, 2010
162010
HARDWARE IMPLEMENTATION OF A TAKAGI-SUGENO NEURO-FUZZY SYSTEM OPTIMIZED BY A POPULATION ALGORITHM
P Dziwinski, A Przybył, P Trippner, J Paszkowski, Y Hayashi
Journal of Artificial Intelligence and Soft Computing Research 11 (3), 243 - 266, 2021
152021
The method of hardware implementation of fuzzy systems on FPGA
A Przybył, MJ Er
Artificial Intelligence and Soft Computing: 15th International Conference …, 2016
142016
The idea for the integration of neuro-fuzzy hardware emulators with real-time network
A Przybył, MJ Er
International Conference on Artificial Intelligence and Soft Computing, 279-294, 2014
122014
Evolutionary approach with multiple quality criteria for controller design
J Szczypta, A Przybył, L Wang
Artificial Intelligence and Soft Computing: 13th International Conference …, 2014
122014
Negative space-based population initialization algorithm (NSPIA)
K Łapa, K Cpałka, A Przybył, K Grzanek
Artificial Intelligence and Soft Computing: 17th International Conference …, 2018
102018
Hard real-time communication solution for mechatronic systems
A Przybył
Robotics and Computer-Integrated Manufacturing 49, 309-316, 2018
102018
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