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A Fuzzy Unscented Kalman Filter in the Adaptive Control System of a Drive System with a Flexible Joint

Author

Listed:
  • Krzysztof Szabat

    (Department of Electrical Drives and Measurements, Wrocław University of Science and Technology, PL50370 Wrocław, Poland)

  • Karol Wróbel

    (Department of Electrical Drives and Measurements, Wrocław University of Science and Technology, PL50370 Wrocław, Poland)

  • Krzysztof Dróżdż

    (Independent Researcher, PL50370 Wrocław, Poland)

  • Dariusz Janiszewski

    (Institute of Robotics and Machine Intelligence, Poznan University of Technology, PL60965 Poznan, Poland)

  • Tomasz Pajchrowski

    (Institute of Robotics and Machine Intelligence, Poznan University of Technology, PL60965 Poznan, Poland)

  • Adrian Wójcik

    (Institute of Robotics and Machine Intelligence, Poznan University of Technology, PL60965 Poznan, Poland)

Abstract

This paper presents an application of an Unscented- and a Fuzzy Unscented- Kalman Filter (UKF and FUKF) to the estimation of mechanical state variables and parameters in a drive system with an elastic connection. The cascade control structure incorporating an IP controller supported by two additional feedbacks and suitable adaptation mechanism is investigated in this study. The coefficients of the control structure are retuned on the basis of the value of mechanical parameters estimated by filter. The effectiveness of the proposed approaches (classical and fuzzy) is researched through simulation and experimental tests.

Suggested Citation

  • Krzysztof Szabat & Karol Wróbel & Krzysztof Dróżdż & Dariusz Janiszewski & Tomasz Pajchrowski & Adrian Wójcik, 2020. "A Fuzzy Unscented Kalman Filter in the Adaptive Control System of a Drive System with a Flexible Joint," Energies, MDPI, vol. 13(8), pages 1-18, April.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:8:p:2056-:d:348057
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    References listed on IDEAS

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    1. Dung Tran Anh & Thang Nguyen Trong, 2018. "Adaptive Controller of the Major Functions for Controlling a Drive System with Elastic Couplings," Energies, MDPI, vol. 11(3), pages 1-11, March.
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    Citations

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    Cited by:

    1. Konrad Urbanski & Dariusz Janiszewski, 2021. "Position Estimation at Zero Speed for PMSMs Using Artificial Neural Networks," Energies, MDPI, vol. 14(23), pages 1-17, December.
    2. Radosław Nalepa & Karol Najdek & Karol Wróbel & Krzysztof Szabat, 2020. "Application of D-Decomposition Technique to Selection of Controller Parameters for a Two-Mass Drive System," Energies, MDPI, vol. 13(24), pages 1-21, December.
    3. Marcin Kaminski & Tomasz Tarczewski, 2023. "Neural Network Applications in Electrical Drives—Trends in Control, Estimation, Diagnostics, and Construction," Energies, MDPI, vol. 16(11), pages 1-25, May.
    4. Karol Wróbel & Kacper Śleszycki & Krzysztof Szabat & Seiichiro Katsura, 2021. "Application of Multilayer Observer for a Drive System with Flexibility," Energies, MDPI, vol. 14(24), pages 1-19, December.
    5. Karol Wróbel & Kacper Śleszycki & Amanuel Haftu Kahsay & Krzysztof Szabat & Seiichiro Katsura, 2023. "Robust Speed Control of Uncertain Two-Mass System," Energies, MDPI, vol. 16(17), pages 1-17, August.
    6. Xiaoyu Deng & Ruo Mo & Pengliang Wang & Junru Chen & Dongliang Nan & Muyang Liu, 2023. "Review of RoCoF Estimation Techniques for Low-Inertia Power Systems," Energies, MDPI, vol. 16(9), pages 1-19, April.
    7. Dominik Łuczak, 2021. "Nonlinear Identification with Constraints in Frequency Domain of Electric Direct Drive with Multi-Resonant Mechanical Part," Energies, MDPI, vol. 14(21), pages 1-12, November.
    8. Marcin Kamiński & Krzysztof Szabat, 2021. "Adaptive Control Structure with Neural Data Processing Applied for Electrical Drive with Elastic Shaft," Energies, MDPI, vol. 14(12), pages 1-26, June.

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    1. Radosław Nalepa & Karol Najdek & Karol Wróbel & Krzysztof Szabat, 2020. "Application of D-Decomposition Technique to Selection of Controller Parameters for a Two-Mass Drive System," Energies, MDPI, vol. 13(24), pages 1-21, December.

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