Mr. Mokhtar Jlidi | Artificial Neural Network | Young Scientist Award
Mr. Mokhtar Jlidi, University of Gabès, Tunisia
Mr. Mokhtar Jlidi, from the University of Gabès in Tunisia, holds a Master’s degree in Research in Automation and Robotic Systems (December 2020) and a Professional Master’s degree in Electrical System Control (July 2018) 🎓. His professional experience includes designing a test bench for turbo-alternator speed regulation at Groupe Chimique Tunisien de Gabes (2018) and developing a photovoltaic generator monitoring prototype (2016) 💼. He also completed internships at Société Tunisienne d’Électricité et de Gaz, gaining valuable experience in electrical production centers. Mr. Jlidi is proficient in programming languages like C, C++, and MATLAB, and skilled in tools like SolidWorks and Dspace 🖥️.
🌐 Professional Profile:
🎓 Education
Mr. Mokhtar Jlidi holds a Master’s degree in Research in Automation and Robotic Systems, which he completed in December 2020 at the Institut Supérieur des Systèmes Industriels de Gabès, Tunisia. He also earned a Professional Master’s degree in Electrical System Control in July 2018 from the same institution.
💼 Professional Experience
From February 2018 to May 2018, Mr. Jlidi worked on his final project at the Groupe Chimique Tunisien de Gabes. His responsibilities included contributing to the design and implementation of a test bench for speed regulation of turbo-alternator groups using the Woodward 505 regulator at the U1000 unit of the phosphoric acid plant.
In February 2016 to April 2016, he undertook another final project at the Institut Supérieur de Systèmes Industriels de Gabès. Here, he designed and developed a prototype for monitoring the characteristics of a photovoltaic generator.
During July 2015 and July 2014, Mr. Jlidi had internships at the Société Tunisienne d’Électricité et de Gaz (STEG), where he gained practical experience in electrical production centers.
🖥️ Skills and Competencies
Mr. Jlidi possesses proficiency in several programming languages including C, C++, STEP7, MATLAB, and Microsoft Office suite. His expertise extends to computer architecture (Windows XP, Vista, Win7), CAD/CAE tools (ISIS, PSIM, MPLAB, ModelSim), SolidWorks, and Dspace.
Publication Top Notes:
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An Artificial Neural Network for Solar Energy Prediction and Control Using Jaya-SMC
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YEAR: 2023
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Synthesis of an Advanced Maximum Power Point Tracking Method for a Photovoltaic System: A Chaotic Jaya Logistic Approach
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YEAR: 2022
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ANN for Temperature and Irradiation Prediction and Maximum Power Point Tracking Using MRP-SMC
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YEAR: 2024
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