dr inż. Daniel Wachowiak
Employment
- Assistant professor at Department of Electric Drives and Energy Conversion
Research fields
Business contact
- Location
- Al. Zwycięstwa 27, 80-219 Gdańsk
- Phone
- +48 58 348 62 62
- biznes@pg.edu.pl
Social media
Contact
- daniel.wachowiak@pg.edu.pl
Assistant professor
- Workplace
-
Budynek A Elektrotech.
room EM-316 open in new tab - Phone
- (58) 347 18 71
- danielw.eia@gmail.com
Publication showcase
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Genetic Algorithm Approach for Gains Selection of Induction Machine Extended Speed Observer
The subject of this paper is gains selection of an extended induction machine speed observer. A high number of gains makes manual gains selection difficult and due to nonlinear equations of the observer, well-known methods of gains selection for linear systems cannot be applied. A method based on genetic algorithms has been proposed instead. Such an approach requires multiple fitness function calls; therefore, using a quality index...
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Fast Real-Time RDFT- and GDFT-Based Direct Fault Diagnosis of Induction Motor Drive
This paper presents the theoretical analysis and experimental verification of a direct fault harmonic identification approach in a converter-fed electric drive for automated diagnosis purposes. On the basis of the analytical model of the proposed real-time direct fault diagnosis, the fault-related harmonic component is calculated using recursive DFT (RDFT) and Goertzel DFT (GDFT), applied instead of the full spectrum calculations...
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A Universal Gains Selection Method for Speed Observers of Induction Machine
Properties of state observers depend on proper gains selection. Each method of state estimation may require the implementation of specific techniques of finding those gains. The aim of this study is to propose a universal method of automatic gains selection and perform its verification on an induction machine speed observer. The method utilizes a genetic algorithm with fitness function which is directly based on the impulse response...
Obtained scientific degrees/titles
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2016-06-21
Obtained science degree
dr inż. Automatic control and robotics (Technology)
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