Controller Design Automation for Power Electronics: A Model-Free Approach

Efficient tools for automating controller design are essential to meet the growing demands of power electronics (PE) applications. Model-based approaches have been widely used for PE controller design, but their design efficiency is often limited by model variations and/or uncertainties and the larg...

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Veröffentlicht in:IEEE transactions on power electronics 2024-02, Vol.39 (2), p.2155-2168
Hauptverfasser: Li, Wanrong, Li, Sinan, Yuan, Huawei, Zhang, Yuhan, Zhu, Jianguo
Format: Artikel
Sprache:eng
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Zusammenfassung:Efficient tools for automating controller design are essential to meet the growing demands of power electronics (PE) applications. Model-based approaches have been widely used for PE controller design, but their design efficiency is often limited by model variations and/or uncertainties and the large design space (DS) that needs to be explored. In this article, we propose a novel model-free design approach based on Fliess's model-free control technique to enable efficient controller design for PE systems. For the first time, we uncover the three key characteristics of Fliess's model-free control. By further exploiting the three characteristics, we can significantly reduce the DS to be explored for optimal control performance, thus reducing the runtime of the design tool. Case studies on a voltage-mode controlled buck converter (with parameter tolerance considered) are performed to demonstrate the effectiveness of the new approach. The new approach shows a runtime speedup of around 100 times compared to the traditional model-based design approach for a small model variation space (MVS) and up to 3000 times for a large MVS while maintaining the accuracy to identify optimal designs that satisfy stability, performance, and robustness requirements. The comparative case studies also exhibit the superiority of our approach using Fliess's model-free control to achieve significant performance improvements in terms of dynamic performance and performance robustness compared to traditional model-based approaches.
ISSN:0885-8993
1941-0107
DOI:10.1109/TPEL.2023.3334861