Author
Abdelrahem, M., Kouzou, A., Kennel, R., Rodriguez, J., Ahmed, M., Makhamreh, Hamza, Harbi, I.
Publication Date
2025-06
Publication Place
-
IEEE
Subject
Predictive control, Multilevel inverter (MLI), Gain-free, Flying capacitor (FC) balance, Current tracking, Hybrid power systems, Industrial electronics, Mathematical models, Regulation, Switching frequency, Inverters, Predictive control, Tuning, Cost function, Topology
Type
Periodical
Language
English
Digital
Yes
Manuscript
No
Library
Özyeğin University
Library Asset ID
0278-0046
Record ID
e479a151-25c8-45fd-a3c5-3d61d0f75d24
Library Location
Electrical & Electronics Engineering
Date
2025-06
Notes
Deutscher Akademischer Austauschdienst ; German Academic Exchange Service ; Technische Universität München ; Agencia Nacional de Investigación y Desarrollo ; Agencia Nacional de Investigación y Desarrollo
Sample Text
Model predictive control (MPC) is a powerful strategy for tackling multiobjective control challenges, but it often involves a laborious process of tuning weighting factors. This article proposes a gain-free MPC method for a recently developed nine-level T-type converter (9L-T-2C), which offers advantages over traditional topologies, such as fewer components and improved efficiency. Drawing inspiration from Lyapunov's theory, this method avoids the use of weighting factors while effectively handling three targets, including current tracking, balancing of flying capacitors (FCs), and regulation of the neutral point (NP). Comparable with the traditional finite-control-set MPC (FCS-MPC), the proposed controller demonstrates high performance concerning all objectives. Additionally, it showcases superior resilience against model uncertainties when compared with the traditional approach. Experimental validation of the proposed MPC method is conducted in grid-connected operation under several conditions. The proposed method is subjected to a comparative analysis via the experimental implementation, where it is compared with a proportional-resonant (PR) controller and other state-of-the- art MPC methods. This analysis reveals the advantages of the proposed method, including eliminating the need for gains or weighting factors, improved robustness, and effective control of the FCs.
DOI
10.1109/TIE.2024.3485627
Cilt
72
