58 / 2025-01-30 18:25:27
A Dual-Vector Predictive Control Method Based on PSO Parameter Identification for NPC Inverters
particle swarm optimization,parameter identification,dual-vector,robustness,model predictive control
摘要录用
Juncheng Zhang / Zhejiang University
Lin Qiu / Zhejiang University
Tingjun Pan / Zhejiang University
Xing Liu / Shanghai Dianji University
Jien Ma / Zhejiang University
Jose Rodriguez / Universidad San Sebastian
Youtong Fang / Zhejiang University
The conventional model predictive control (MPC) is highly dependent on load parameters and has limited robustness. In this paper, a dual-vector model predictive control algorithm based on particle swarm optimization (PSO) for parameter identification is proposed. The PSO algorithm is used to identify the load parameters, while the dual-vector method enhances the prediction accuracy and robustness. MATLAB/Simulink is used for simulation analysis, and experiments are conducted to validate the effectiveness of the proposed method.
重要日期
  • 会议日期

    06月05日

    2025

    06月08日

    2025

  • 04月30日 2025

    初稿截稿日期

主办单位
IEEE PELS
IEEE
承办单位
Southeast University
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