Application of fuzzy type II multi-layer Kalman filter for parameters identification of two-mass drive system

• Autorzy: Śleszycki Kacper , Wróbel Karol , Szabat Krzysztof , Katsura Seiichiro

Identyfikatory

DOI

10.24425/bpasts.2023.146107

• Języki publikacji: EN

Abstrakty

EN

The paper describes a novel online identification algorithm for a two-mass drive system. The multi-layer extended Kalman Filter (MKF) is proposed in the paper. The proposed estimator has two layers. In the first one, three single extended Kalman filters (EKF) are placed. In the second layer, based on the incoming signals from the first layer, the final states and parameters of the two-mass system are calculated. In the considered drive system, the stiffness coefficient of the elastic shaft and the time constant of the load machine is estimated. To improve the quality of estimated states, an additional system based on II types of fuzzy sets is proposed. The application of fuzzy MKF allows for a shorter identification time, as well as improves the accuracy of estimated parameters. The identified parameters of the two-mass system are used to calculate the coefficients of the implemented control structure. Theoretical considerations are supported by simulations and experimental tests.

Słowa kluczowe

EN

electrical drives; torsional vibration; state estimation; Kalman filter; multi-layer estimator

PL

napędy elektryczne; drgania skrętne; ocena stanu; estymator wielowarstwowy; filtr Kalmana

• Wydawca: Polska Akademia Nauk, Wydział IV Nauk Technicznych
• Czasopismo: Bulletin of the Polish Academy of Sciences. Technical Sciences
• Rocznik: 2023
• Tom: Vol. 71, nr 4
• Strony: art. no. e146107
• Opis fizyczny: Bibliogr. 32 poz., rys., tab.

Twórcy

autor

Śleszycki Kacper

• Wrocław University of Science and Technology, Institute of Electrical Machines, Drives and Measurements, Wrocław, Poland

• https://orcid.org/0000-0002-8764-4137

autor

Wróbel Karol

• Wrocław University of Science and Technology, Institute of Electrical Machines, Drives and Measurements, Wrocław, Poland

• https://orcid.org/0000-0002-7095-1384

autor

Szabat Krzysztof

• Wrocław University of Science and Technology, Institute of Electrical Machines, Drives and Measurements, Wrocław, Poland

• https://orcid.org/0000-0001-8473-9475

autor

Katsura Seiichiro

• Keio University, Department of System Design Engineering, Tokyo, Japan

• https://orcid.org/0000-0002-7487-0610

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Uwagi

Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2022-2023).