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The Study of Fuzzy Proportional Integral Controllers Based on Improved Particle Swarm Optimization for Permanent Magnet Direct Drive Wind Turbine Converters

Author

Listed:
  • Yancai Xiao

    (School of Mechanical, Electronic and Control Engineering, Beijing Jiaotong University, Beijing 100044, China)

  • Tieling Zhang

    (School of Mechanical, Materials and Mechatronic Engineering, University of Wollongong, Northfields Ave, Wollongong, NSW 2522, Australia)

  • Zeyu Ding

    (School of Mechanical, Electronic and Control Engineering, Beijing Jiaotong University, Beijing 100044, China
    These authors contributed equally to this work.)

  • Chunya Li

    (School of Mechanical, Electronic and Control Engineering, Beijing Jiaotong University, Beijing 100044, China
    These authors contributed equally to this work.)

Abstract

In order to meet the requirements of high precision and fast response of permanent magnet direct drive (PMDD) wind turbines, this paper proposes a fuzzy proportional integral (PI) controller associated with a new control strategy for wind turbine converters. The purpose of the control strategy is to achieve the global optimization for the quantization factors, k e and k ec , and scale factors, k up and k ui , of the fuzzy PI controller by an improved particle swarm optimization (PSO) method. Thus the advantages of the rapidity of the improved PSO and the robustness of the fuzzy controller can be fully applied in the control process. By conducting simulations for 2 MW PMDD wind turbines with Matlab/Simulink, the performance of the fuzzy PI controller based on the improved PSO is demonstrated to be obviously better than that of the PI controller or the fuzzy PI controller without using the improved PSO under the situation when the wind speed changes suddenly.

Suggested Citation

  • Yancai Xiao & Tieling Zhang & Zeyu Ding & Chunya Li, 2016. "The Study of Fuzzy Proportional Integral Controllers Based on Improved Particle Swarm Optimization for Permanent Magnet Direct Drive Wind Turbine Converters," Energies, MDPI, vol. 9(5), pages 1-17, May.
    • Handle: RePEc:gam:jeners:v:9:y:2016:i:5:p:343-:d:69526
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    References listed on IDEAS

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    5. Bououden, S. & Chadli, M. & Filali, S. & El Hajjaji, A., 2012. "Fuzzy model based multivariable predictive control of a variable speed wind turbine: LMI approach," Renewable Energy, Elsevier, vol. 37(1), pages 434-439.
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    Citations

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    Cited by:

    1. Yancai Xiao & Yi Hong & Xiuhai Chen & Wenjian Huo, 2016. "Switching Control of Wind Turbine Sub-Controllers Based on an Active Disturbance Rejection Technique," Energies, MDPI, vol. 9(10), pages 1-19, October.
    2. Qixiang Yan & Ibrahim Adamu Tasiu & Hong Chen & Yuting Zhang & Siqi Wu & Zhigang Liu, 2019. "Design and Hardware-in-the-Loop Implementation of Fuzzy-Based Proportional-Integral Control for the Traction Line-Side Converter of a High-Speed Train," Energies, MDPI, vol. 12(21), pages 1-24, October.
    3. Fausto Pedro García Márquez & Alberto Pliego Marugán & Jesús María Pinar Pérez & Stuart Hillmansen & Mayorkinos Papaelias, 2017. "Optimal Dynamic Analysis of Electrical/Electronic Components in Wind Turbines," Energies, MDPI, vol. 10(8), pages 1-19, July.
    4. Xing Liu & Jinhua Du & Deliang Liang, 2016. "Analysis and Speed Ripple Mitigation of a Space Vector Pulse Width Modulation-Based Permanent Magnet Synchronous Motor with a Particle Swarm Optimization Algorithm," Energies, MDPI, vol. 9(11), pages 1-15, November.
    5. Giovanni Pau & Mario Collotta & Vincenzo Maniscalco, 2017. "Bluetooth 5 Energy Management through a Fuzzy-PSO Solution for Mobile Devices of Internet of Things," Energies, MDPI, vol. 10(7), pages 1-22, July.
    6. He-Yau Kang & Amy H. I. Lee & Tzu-Ting Huang, 2016. "Project Management for a Wind Turbine Construction by Applying Fuzzy Multiple Objective Linear Programming Models," Energies, MDPI, vol. 9(12), pages 1-15, December.
    7. Lei Chen & Xiude Tu & Hongkun Chen & Jun Yang & Yayi Wu & Xin Shu & Li Ren, 2016. "Technical Evaluation of Superconducting Fault Current Limiters Used in a Micro-Grid by Considering the Fault Characteristics of Distributed Generation, Energy Storage and Power Loads," Energies, MDPI, vol. 9(10), pages 1-21, September.

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