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Model-Free Predictive Control for Improved Performance and Robustness of Three-Phase Quasi Z-Source Inverters

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  • Additional Information
    • Publication Date:
      2024
    • Collection:
      Aalborg University (AAU): Publications / Aalborg Universitet: Publikationer
    • Abstract:
      This paper suggests a novel Model-Free Predictive Control (MFPC) approach for three-phase quasi Z-source inverters (qZSI). While Model Predictive Control (MPC) is popular for qZSI due to its ease of use and performance, it suffers from sensitivity to parameter mismatch. The proposed MFPC overcomes this limitation by relying on an ultra-local model (ULM), eliminating the need for precise parameter matching. This approach establishes a comprehensive mathematical model for key qZSI control variables, including load current, inductor current, and capacitor voltage. Additionally, a unique method seamlessly integrates shoot-through status into the MFPC framework without compromising qZSI operation. Simulation results across various operating conditions demonstrate how much better the suggested MFPC is than the traditional MPC, especially under parameter mismatch scenarios. Notably, the MFPC achieves a significant improvement, exceeding a 37% reduction in total harmonic distortion (THD). Furthermore, the practicality of the proposed MFPC strategy is validated through hardware-in-the-loop (HIL) testing using a C2000TM microcontroller.
    • File Description:
      application/pdf
    • Accession Number:
      10.1109/ACCESS.2024.3417397
    • Online Access:
      https://vbn.aau.dk/da/publications/7b9aacb3-5b68-4187-845c-44dd0f509da6
      https://doi.org/10.1109/ACCESS.2024.3417397
      https://vbn.aau.dk/ws/files/725457132/Model-Free_Predictive_Control_for_Model_free_predictive_with_Improved_Performance_and_Robustness_of_Three-Phase_Quasi_Z-Source_Inverters.pdf
      http://www.scopus.com/inward/record.url?scp=85196716122&partnerID=8YFLogxK
      https://ieeexplore.ieee.org/document/10568137
    • Rights:
      info:eu-repo/semantics/openAccess
    • Accession Number:
      edsbas.850CC3E0