Model Predictive Control of Multilevel Inverters: Challenges, Recent Advances, and Trends
Harbi, Ibrahim; Rodriguez, Jose; Liegmann, Eyke; Makhamreh, Hamza; Heldwein, Marcelo Lobo; Novak, Mateja; Rossi, Mattia; Abdelrahem, Mohamed; Trabelsi, Mohamed; Ahmed, Mostafa; Karamanakos, Petros; Xu, Shuai; Dragicevic, Tomislav; Kennel, Ralph (2023)
Harbi, Ibrahim
Rodriguez, Jose
Liegmann, Eyke
Makhamreh, Hamza
Heldwein, Marcelo Lobo
Novak, Mateja
Rossi, Mattia
Abdelrahem, Mohamed
Trabelsi, Mohamed
Ahmed, Mostafa
Karamanakos, Petros
Xu, Shuai
Dragicevic, Tomislav
Kennel, Ralph
2023
IEEE Transactions on Power Electronics
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Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:tuni-202309078019
https://urn.fi/URN:NBN:fi:tuni-202309078019
Kuvaus
Peer reviewed
Tiivistelmä
<p>Model predictive control (MPC) has emerged as a promising control method in power electronics, particularly for multi-objective control problems such as multilevel inverter (MLI) applications. Over the past two decades, improving the performance of MPC and tackling its technical challenges such as computational load, modeling accuracy, cost function design and weighting factors selection have attracted great interest in power electronics. This article aims to discuss the current state of MPC strategies for MLI applications, describing the significance of each challenge with the reported effective solutions. Through this review, the MPC methods are categorized into two groups, direct MPC (without modulator) and indirect MPC (with modulator). The recent advances of each category are presented and analyzed, focusing on direct MPC as the most applied method for MLI topologies. In addition, some of the important concepts are experimentally validated through a case study and compared under the same operating conditions to evaluate the performance and highlight their features. Finally, the future trends of MPC for MLI applications are discussed based on the current state and reported developments.</p>
Kokoelmat
- TUNICRIS-julkaisut [20173]