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<p>Phase-locked loops (PLLs) are often applied in speed estimation. However, PLLs suffer from certain problems, such as poor dynamic performance and complex parameter tuning, due to their structural design, and both issues are difficult to simultaneously address. This work proposes a fixed-gain filter-based phase-locked loop (FGF-PLL) to address this concern. The FGF-PLL fixes the gain matrix of the Kalman filter to a constant to minimize the computational burden. Meanwhile, only one adjustable parameter exists in the fixed-gain matrix, and its value can be confined to a narrow range through stability analysis. Consequently, the parameter tuning process is more straightforward than that of the conventional PLL. The superiority of the proposed FGF-PLL is experimentally validated using a permanent magnet synchronous machine. </p>

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Fixed-gain filter-based phase-locked loop for sensorless control of synchronous machines

  • 期刊论文

  • 发表日期：

    2025年6月23日

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  • Zhixun Ma,
  • Jian Huang,
  • Haichuan Niu,
  • Xiang Wu,
  • Xu Zhang,
  • Xinbo Cai

摘要

Phase-locked loops (PLLs) are often applied in speed estimation. However, PLLs suffer from certain problems, such as poor dynamic performance and complex parameter tuning, due to their structural design, and both issues are difficult to simultaneously address. This work proposes a fixed-gain filter-based phase-locked loop (FGF-PLL) to address this concern. The FGF-PLL fixes the gain matrix of the Kalman filter to a constant to minimize the computational burden. Meanwhile, only one adjustable parameter exists in the fixed-gain matrix, and its value can be confined to a narrow range through stability analysis. Consequently, the parameter tuning process is more straightforward than that of the conventional PLL. The superiority of the proposed FGF-PLL is experimentally validated using a permanent magnet synchronous machine.