A neural-enhanced active disturbance load-side speed control of an electric drive with a flexible link

• Autorzy: Kaczmarczyk Grzegorz , Stanislawski Radoslaw , Kaminski Marcin , Kasprzak Kacper , Ferreira Danton Diego

Identyfikatory

DOI

10.24425/aee.2025.153024

• Języki publikacji: EN

Abstrakty

EN

The paper is focused on improvements of the conventional speed controller based on Active Disturbance Rejection Control (ADRC) applied for a two-mass electric drive system. The described ADRC structure is based on load-side speed measurement. The paper compares conventional structure dynamics with overall system behavior in the case plant parameters are changed. The proposed ADRC algorithm extension performs soft controller parameters adjustment to improve the dynamics and plant response. The presented approach accomplishes adaptation capabilities with the use of a Radial Basis Function Neural Network (RBFNN). The article presents the dynamic response of the plant controlled by the conventional ADRC algorithm and the designed neural adaptation extension. The results are based on the performed experimental tests.

Słowa kluczowe

EN

active disturbance rejection control; adaptive control; electric drive; neural network; two-mass system

• Wydawca: Polish Academy of Sciences, Committee on Electrical Engineering
• Czasopismo: Archives of Electrical Engineering
• Rocznik: 2025
• Tom: Vol. 74, nr 1
• Strony: 269--289
• Opis fizyczny: Bibliogr. 24 poz., fot., rys., wz.

Twórcy

autor

Kaczmarczyk Grzegorz

• Wroclaw University of Science and Technology, Poland

• https://orcid.org/0009-0002-4059-9540

autor

Stanislawski Radoslaw

• Wroclaw University of Science and Technology, Poland

• https://orcid.org/0000-0003-4739-2948

autor

Kaminski Marcin

• Wroclaw University of Science and Technology, Poland

• https://orcid.org/0000-0002-8472-1053

autor

Kasprzak Kacper

• Poznan University of Technology, Poland

• https://orcid.org/0009-0001-5641-6449

autor

Ferreira Danton Diego

• Federal University of Lavras, Brazil

• https://orcid.org/0000-0002-4504-7721

Bibliografia

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Uwagi

Opracowanie rekordu ze środków MNiSW, umowa nr POPUL/SP/0154/2024/02 w ramach programu "Społeczna odpowiedzialność nauki II" - moduł: Popularyzacja nauki (2025).