Inverse Model Predictive Voltage-Control for Triple Active Bridge Converters With Coupling Effects Mitigation

Bayindir A. B., Sharida A., Bayhan S., Abu-Rub H., Begovic M.

IEEE Transactions on Industrial Electronics, 2026 (SCI-Expanded, Scopus)

  • Yayın Türü: Makale / Tam Makale
  • Basım Tarihi: 2026
  • Doi Numarası: 10.1109/tie.2026.3706872
  • Dergi Adı: IEEE Transactions on Industrial Electronics
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Aerospace Database, Compendex, INSPEC, Materials Science & Engineering Collection (ProQuest), Technology Collection (ProQuest)
  • Anahtar Kelimeler: Coupling effect (CE) estimation, decoupling control, inverse model predictive control (IMPC), triple active bridge (TAB)
  • Gazi Üniversitesi Adresli: Evet

Özet

The coupling effects (CEs) and complex dynamic modeling of isolated multiport DC–DC converters (IMDCs) remain a key barrier to accelerating their adoption. The main objective of this article is to address these challenges, while simultaneously achieving accurate voltage regulation and robustness against parameter uncertainties in IMDCs. This article proposes an adaptive control technique for triple active bridge (TAB) converters based on inverse model predictive control (IMPC), along with the coupling-effects estimation and mitigation. The CEs in the TAB converters affect the system response by introducing nonlinear interactions between ports, leading to increased uncertainties in the dynamic model. To mitigate these interactions, a coupling-effects observer is first developed. The designed observer depends on the difference between measured and predicted voltages to estimate the CEs along with any unmodeled dynamics. By leveraging the estimation from the observer, the IMPC algorithm adaptively compensates for CEs, ensures precise voltage regulation, and rejects disturbances. The proposed control mechanism is experimentally implemented using a low-cost microcontroller, and the results show a superior behavior of the proposed approach against conventional model predictive control (MPC) and IMPC approaches.