Mohamed Trabelsi

Bio: Mohamed Trabelsi is an academic researcher from Lehigh University. The author has contributed to research in topics: Inverter & Model predictive control. The author has an hindex of 25, co-authored 216 publications receiving 2302 citations. Previous affiliations of Mohamed Trabelsi include Institut national des sciences Appliquées de Lyon & Texas A&M University at Qatar.

A Selective Frequency-Reconfigurable Antenna for Cognitive Radio Applications

Abstract: This letter presents a selective frequency-reconfigurable antenna, suitable for cognitive radio applications. The proposed antenna is capable of switching between a wide operating band of 2.63-3.7 GHz and four different subbands, which allows using it for sensing the entire band and then adjusting its bandwidth to select the suitable sub-band and prefilter out the other ones. The antenna is composed of a radiating element in the form of an inverted U fed by a microstrip line on its upper side. In order to achieve a selective frequency reconfiguration, four horizontal slots with integrated p-i-n diode switches are incorporated in the ground plane to act as reconfigurable filter. Some of the switches are used to alter the antenna bandwidth, while the others are employed to shift the operating band by varying the electrical length of the middle slots. To present the work, both simulated and measured results are presented, and a good agreement is achieved.

Finite-Control-Set Model Predictive Control for Grid-Connected Packed-U-Cells Multilevel Inverter

Abstract: This paper presents a finite-control-set model predictive control (FCS-MPC) for grid-tied packed U cells (PUC) multilevel inverter (MLI). The system under study consists of a single-phase 3-cells PUC inverter connected to the grid through filtering inductor. The proposed competitive topology allows the generation of 7-level output voltage with reduction of passive and active components compared to the conventional MLIs. The aim of the proposed FCS-MPC technique is to achieve, under various operating conditions, grid-tied current injection with unity power factor and low total harmonic distortion while balancing the capacitor voltage. Parameters’ sensitivity analysis was also conducted. The study is conducted on a low-power case study single-phase 3-cells PUC inverter and with possible extension to higher number of cells. Theoretical analysis, simulation, and experimental results are presented and compared.

Modular Multilevel Converter Circulating Current Reduction Using Model Predictive Control

Abstract: Modular multilevel converter (MMC) is a promising new topology for high-voltage applications. The MMC is made of several identical submodules. For proper operation, each submodule can be considered as a controlled voltage source where capacitor’s voltage should be maintained at a certain level. Besides, the minimization of the circulating current, which does not flow to the load, is crucial for achieving stable and efficient operation of the MMC. The interrelations among the load current, circulating current, and capacitor voltages complicate the MMC control. This paper aims to achieve stable and balanced voltage and current control with reduced circulating current in various operating conditions. The proposed control uses weighted model predictive control based on a normalized cost function to select the inverter switching patterns, which control the load current, while minimizing voltage fluctuation and circulating current. The weighting factors were selected based on minimizing the load-current total harmonic distortion (THD) and circulating current. The analysis is conducted on a low-power case study of single-phase four-cells MMC with possible extension to higher number of cells. The low-power three-level prototype is designed and built to validate this proposed method. Theoretical analysis, simulation, and experimental results are presented and compared. Parameter sensitivity analysis was also conducted. They all confirm the effectiveness of the proposed control method.

Finite-Control-Set Model-Predictive Control for a Quasi-Z-Source Four-Leg Inverter Under Unbalanced Load Condition

Abstract: This paper presents finite-control-set model-predictive control (FCS-MPC) for a three-phase quasi-Z-source (qZS) four-leg inverter under unbalanced load condition. The key novelty of the proposed control approach is eliminating the double-line frequency ripple in the inductor current with a simple and effective approach. The proposed four-leg qZS inverter with an output $LC$ filter can handle buck/boost and dc/ac conversion features in a single stage. Furthermore, the FCS-MPC-based control algorithm helps in maintaining balanced point of common coupling voltages for stand-alone unbalanced loads. The behavior of the predictive controller has been investigated under different operating conditions, and its robustness with the qZS network and the $LC$ filter parameter variations are also studied. Furthermore, the effect of double-line frequency ripple and its relation with the inductor current constraint have been tackled comprehensively. To verify the performance of the proposed approach, simulation and experimental studies were performed for balanced and unbalanced loads.

Precautionary Saving in the Small and in the Large

Abstract: The theory of precautionary saving is shown in this paper to be isomorphic to the Arrow-Pratt theory of risk aversion, making possible the application of a large body of knowledge about risk aversion to precautionary saving, and more generally, to the theory of optimal choice under risk In particular, a measure of the strength of precautionary saving motive analogous to the Arrow-Pratt measure of risk aversion is used to establish a number of new propositions about precautionary saving, and to give a new interpretation of the Oreze-Modigliani substitution effect