Browsing by Author "Trabelsi, M."

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Lyapunov-based model predictive control for stable operation of a 9-level crossover switches cell inverter in grid connection mode
(IEEE, 2023) Trabelsi, M.; Makhamreh, Hamza; Alquennah, A. N.; Vahedi, H.; Electrical & Electronics Engineering; MAKHAMREH, Hamza Ahmed Mousa
This study proposes the application of a Lyapunov-based Model Predictive Control (L-MPC) approach to a 9-level Crossover Switches Cell (CSC9) converter operating in grid connection mode. The proposed method utilizes the structure of the classical finite-control-set MPC (FCS-MPC) technique while integrating a cost function that requires no tuning. By deriving the cost function based on Lyapunov theory, the system stability is ensured. Notably, the suggested approach offers several advantages over traditional MPC controllers. Firstly, it eliminates the need for gain tuning, thereby simplifying the implementation process. Secondly, the proposed controller prioritizes stability as a key design aspect. The presented simulation results prove that the proposed controller effectively regulates the voltage of the DC capacitor around its desired value and feed a smooth sinusoidal current to the grid with low total harmonic distortion (THD) while operating at a unity power factor.
Open Access
Model predictive control of a PUC5-based dual-output electric vehicle battery charger
(MDPI, 2023-10) Makhamreh, Hamza; Kanzari, M.; Trabelsi, M.; Electrical & Electronics Engineering; MAKHAMREH, Hamza Ahmed Mousa
In this study, a model predictive control (MPC) technique is applied to a packed-u-cell (PUC)-based dual-output bidirectional electric vehicle (EV) battery charger. The investigated topology is a 5-level PUC-based power factor correction (PFC) rectifier allowing the generation of two levels of DC output voltages. The optimization of the MPC cost function is performed by reducing the errors on the capacitors’ voltages (DC output voltages) and the grid (input) current. Moreover, the desired capacitors’ voltages and peak value of the input current are considered within the designed cost function to normalize the errors. In addition, an external PI controller is used to generate the amplitude of the grid current reference based on the computed errors on the capacitors’ voltages. The presented simulation and experimental results recorded using a 1 kW laboratory prototype demonstrate the high performance of the proposed approach in rectifying the AC source at different levels (dual rectifier), while drawing a sinusoidal current from the grid with low THD (around 4%) and ensuring a unity power factor operation.
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Model-predictive control of multilevel inverters: challenges, recent advances, and trends
(IEEE, 2023-09) Harbi, I.; Rodriguez, J.; Liegmann, E.; Makhamreh, Hamza; Heldwein, M. L.; Novak, M.; Rossi, M.; Abdelrahem, M.; Trabelsi, M.; Ahmed, M.; Karamanakos, P.; Xu, S.; Electrical & Electronics Engineering; MAKHAMREH, Hamza Ahmed Mousa
Model-predictive control (MPC) has emerged as a promising control method in power electronics, particularly for multiobjective 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 factor 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.