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<p>In conventional finite-control-set model predictive control (FCS-MPC) for NPC-type grid-connected inverters, issues such as large output current harmonics and poor parameter robustness are prevalent. To address these challenges, this article presents a novel model-free predictive control method with dual vector. The proposed approach constructs an ultra-local model of the system and uses an adaptive sliding-mode observer to estimate the lumped disturbance, eliminating the reliance on precise system parameters and thereby enhancing robustness. Additionally, an equivalent two-level vector set is established, reducing the number of candidate voltage vectors to six, which significantly simplifies the rolling optimization process. Furthermore, the approach employs two voltage vectors in each control cycle, effectively reducing the current tracking error and consequently lowering the current harmonics. Experimental results show that the proposed method delivers excellent robustness and reduces current harmonics, offering a promising solution for enhancing the performance of NPC-type grid-connected inverters.</p>

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Model-free predictive control method with dual vector for NPC-type grid-connected inverters

  • 期刊论文

  • 发表日期：

    2025年4月10日

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  • Hongxun Liu,
  • Yilin Meng,
  • Wenhua Li,
  • Jiyuan Cai,
  • Jihui Gao

摘要

In conventional finite-control-set model predictive control (FCS-MPC) for NPC-type grid-connected inverters, issues such as large output current harmonics and poor parameter robustness are prevalent. To address these challenges, this article presents a novel model-free predictive control method with dual vector. The proposed approach constructs an ultra-local model of the system and uses an adaptive sliding-mode observer to estimate the lumped disturbance, eliminating the reliance on precise system parameters and thereby enhancing robustness. Additionally, an equivalent two-level vector set is established, reducing the number of candidate voltage vectors to six, which significantly simplifies the rolling optimization process. Furthermore, the approach employs two voltage vectors in each control cycle, effectively reducing the current tracking error and consequently lowering the current harmonics. Experimental results show that the proposed method delivers excellent robustness and reduces current harmonics, offering a promising solution for enhancing the performance of NPC-type grid-connected inverters.