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Titel:

Model-Free Predictive Control Based on Data-Driven for Fast and Accurate Power Allocation in Solid-State DC Transformers

Dokumenttyp:
Zeitschriftenaufsatz
Autor(en):
Dehao Kong; Shaobin Li; Chuang Liu; Zhenbin Zhang; Yuanxiang Sun; Ralph Kennel; Marcelo Lobo Heldwein
Abstract:
Robustness is a crucial issue in model predictive control (MPC) despite the excellent dynamic performance and effective management of multiple variables that this control strategy provides for converters. This challenging is particularly concerning in solid-state DC transformers (DCT) connected as input-series-output-parallel modules because this type of DCT not only regulates the output voltage/power but also balances the input voltage so that the power is averagely distributed among sub-module...     »
Stichworte:
Autoregressive processes, Predictive models, Analytical models, Voltage control, Predictive control, Discrete cosine transforms, Adaptation models, Solid-state DC transformer, Model-free predictive control, adaptive balance controller
Zeitschriftentitel:
IEEE Transactions on Power Electronics
Jahr:
2024
Jahr / Monat:
2024-08
Quartal:
3. Quartal
Monat:
Aug
Heft / Issue:
( Early Access )
Reviewed:
ja
Sprache:
en
Volltext / DOI:
doi:10.1109/TPEL.2024.3448243
Print-ISSN:
0885-8993
E-ISSN:
1941-0107
Publikationsdatum:
22.08.2024
Copyright Informationen:
(c) IEEE
Semester:
SS 24
TUM Einrichtung:
Lehrstuhl für Hochleistungs-Umrichtersysteme
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