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All Journal International Journal of Electrical and Computer Engineering International Journal of Power Electronics and Drive Systems (IJPEDS) IAES International Journal of Artificial Intelligence (IJ-AI) Bulletin of Electrical Engineering and Informatics
Mouhsen, Ahmed
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Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering

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Journal : International Journal of Electrical and Computer Engineering

 1 
A new compact grounded coplanar waveguide slotted multiband planar antenna for radio frequency identification data applications Dakir, Rachid; Mouhsen, Ahmed
International Journal of Electrical and Computer Engineering (IJECE) Vol 12, No 4: August 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v12i4.pp3800-3807

Abstract

This research presents the development and conception of a new compact grounded coplanar waveguide fed slotted rectangular planar antenna with a multi-frequency band for radio frequency identification data (RFID) reader applications which is based on the antenna mono-band frequency to use for a various applications RFID to support a different operating range. The optimized of the final prototype designing operates a multiple frequency bands ranging from 0.7-1.1 GHz, 2.2-2.5 GHz and 5.4-6 GHz for 0.9/2.4 GHz and 5.8 GHz RFID operation bands which is adapted from ultra-high frequency band (0.9 GHz) to microwave frequency band (2.4-5.8 GHz) RFID systems. This antenna is implemented and printed on a FR4 substrate with a size of 30×50×1.6 mm3. The novel prototype includes of a radiator rectangular patch with a symmetrical slot and a U-slot with I-stub on ground plan. The principles parameters of the antenna have been studied optimized and miniaturized by using a two simulators CST Microwave Studio and advanced design system (ADS) to validate the simulation results before the planar antenna realization. The final structure is achieved and validated of the results measurement. Experimental results show that the proposed antenna with a small size has good and stable radiation and thus promising for a various RFID applications.
Nonlinear backstepping and model predictive control for grid-connected permanent magnet synchronous generator wind turbines Kassoumi, Adil El; Lamhamdi, Mohamed; Mouhsen, Ahmed; Fdaili, Mohammed; Aboudrar, Imad; Mouhsen, Azeddine
International Journal of Electrical and Computer Engineering (IJECE) Vol 15, No 6: December 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v15i6.pp5091-5105

Abstract

This research investigates and compares two nonlinear current-control strategies, backstepping control (BSC) and finite control set model predictive control (FCS-MPC) for machine-side and grid-side converters in grid-connected direct-drive permanent magnet synchronous generator (DD-PMSG) wind turbines. Addressing the control challenges in wind energy systems with varying speeds, the study aims to determine which strategy offers superior performance under identical operating conditions. The nonlinear BSC regulates stator and grid currents using Lyapunov-based techniques, while FCS-MPC leverages model predictions to select optimal switching states based on a cost function. A comprehensive simulation using MATLAB/Simulink is conducted, analyzing each controller’s transient behavior, steady-state response, torque ripple, and power quality total harmonic distortion (THD). Results show that FCS-MPC achieves faster convergence, lower overshoot, and superior power quality compared to BSC, though it requires higher computational resources. Statistical validation supports the robustness of FCS-MPC under parameter uncertainties. This work contributes a structured comparison of advanced nonlinear strategies for PMSG-based wind turbines and provides a foundation for future implementations in real-time embedded control systems. Future directions include experimental validation and hybrid model predictive controller- artificial intelligence (MPC-AI) control frameworks.
AI-MG-LEACH: investigation of MG-LEACH in wireless sensor networks energy efficiency applied the advanced algorithm Ouldzira, Hicham; Essaadoui, Alami; Hanine, Mustapha EL; Mouhsen, Ahmed; Mes-Adi, Hassane
International Journal of Electrical and Computer Engineering (IJECE) Vol 15, No 6: December 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v15i6.pp5080-5090

Abstract

Wireless sensor networks (WSNs) play a crucial role in data collection across various fields like environmental monitoring and industrial automation. The energy efficiency of these networks, powered by limited-capacity batteries, is key to their performance. Clustering protocols such as low- energy adaptive clustering hierarchy (LEACH) are widely used to optimize energy consumption. To enhance LEACH’s performance, MG-LEACH was introduced, improving cluster head selection to extend network lifespan. This study compares MG-LEACH with AI-MG-LEACH, which incorporates artificial intelligence (AI) to further improve energy efficiency by selecting cluster heads based on factors like residual energy. Simulations show AI-MG-LEACH reduces energy consumption, extends network life, and enhances data reliability, outperforming MG-LEACH.
Co-Authors Aboudrar, Imad Dakir, Rachid El Farnane, Abdelhafid El Ihyaoui, Abdelilah Ennajih, Elmehdi Ennaoui, Ilias Essaadoui, Alami Farchi, Mohamed Fdaili, Mohammed Hanine, Mustapha EL Jarmouni, Ezzitouni Kassoumi, Adil El Krari, Ayoub Lamhamdi, Mohamed Mes-Adi, Hassane Mouhsen, Azeddine Ouldzira, Hicham Tahiry, Karim Youssefi, My Abdelkader