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Design and Verification of the LQR Controller Based on Fuzzy Logic for Large Wind Turbine

Author

Listed:
  • Taesu Jeon

    (Department of Integrated Energy & Infra System, Kangwon National University, Chuncheon 24341, Gangwon, Korea)

  • Insu Paek

    (Department of Integrated Energy & Infra System, Kangwon National University, Chuncheon 24341, Gangwon, Korea
    Department of Mechatronics Engineering, Kangwon National University, Chuncheon 24341, Gangwon, Korea)

Abstract

In this study, a linear quadratic regulator based on the fuzzy logic (LQRF) control algorithm for a variable-speed variable-pitch wind turbine was designed. In addition, to verify the optimum performance of the controller, simulations and wind tunnel tests were conducted. In the simulation, the performances of the proportional-integral (PI) and LQRF algorithms were compared in the transition region and the rated power region. In the wind tunnel test, the applicability of the LQRF algorithm was verified by comparing it with the conventional PI algorithms. The results showed that when compared with the PI control, the proposed LQRF control reduced the tower vibration by up to 12.50% depending on the operating region. Furthermore, the power deviation was reduced by 38.93%. These tests confirmed that the proposed LQRF control increases the power performance and structural stability of wind turbines compared with conventional PI controls.

Suggested Citation

  • Taesu Jeon & Insu Paek, 2021. "Design and Verification of the LQR Controller Based on Fuzzy Logic for Large Wind Turbine," Energies, MDPI, vol. 14(1), pages 1-17, January.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:1:p:230-:d:474639
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    References listed on IDEAS

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    1. Kwansu Kim & Hyun-Gyu Kim & Yuan Song & Insu Paek, 2019. "Design and Simulation of an LQR-PI Control Algorithm for Medium Wind Turbine," Energies, MDPI, vol. 12(12), pages 1-18, June.
    2. Sungsu Park & Yoonsu Nam, 2012. "Two LQRI based Blade Pitch Controls for Wind Turbines," Energies, MDPI, vol. 5(6), pages 1-19, June.
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    Cited by:

    1. Taesu Jeon & Dongmyoung Kim & Yuan Song & Insu Paek, 2021. "Design and Validation of Demanded Power Point Tracking Control Algorithm for MIMO Controllers in Wind Turbines," Energies, MDPI, vol. 14(18), pages 1-18, September.
    2. Mateusz Kozek & Adam Smoter & Krzysztof Lalik, 2023. "Neural-Assisted Synthesis of a Linear Quadratic Controller for Applications in Active Suspension Systems of Wheeled Vehicles," Energies, MDPI, vol. 16(4), pages 1-17, February.
    3. Donggeun Jeong & Taesu Jeon & Insu Paek & Deokjin Lim, 2023. "Development and Validation of Control Algorithm for Variable Speed Fixed Pitch Small Wind Turbine," Energies, MDPI, vol. 16(4), pages 1-18, February.
    4. Miloš Milašinović & Damjan Ivetić & Milan Stojković & Dragan Savić, 2023. "Failure Conditions Assessment of Complex Water Systems Using Fuzzy Logic," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 37(3), pages 1153-1182, February.
    5. Taesu Jeon & Dongmyoung Kim & Insu Paek, 2022. "Improvements to and Experimental Validation of PI Controllers Using a Reference Bias Control Algorithm for Wind Turbines," Energies, MDPI, vol. 15(21), pages 1-18, November.

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