Ms.Yattou El Fadili | Renewable energy | Best Researcher Award

Doctoral Student at Sidi Mohamed Ben Abdellah University, Morocco

Yattou EL FADILI is a dedicated doctoral researcher affiliated with the Faculty of Sciences Dhar El Mahraz, Sidi Mohamed Ben Abdellah University in Morocco. Her work focuses on renewable energy, with an emphasis on advanced control systems for wind turbine energy conversion. With an impressive academic background, including a B.Sc. in physics and an M.Sc. in microelectronics, signals, and systems, she has authored impactful publications and presented her research at prestigious international conferences. Her expertise spans topics like robust stability, Lyapunov stability theory, state-feedback control, and genetic algorithms, making her a promising candidate for this award.

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Education

Yattou EL FADILI completed her Bachelor of Science in Physics with an Electronic Option in 2019 at the Faculty of Sciences Dhar El Mahraz, Sidi Mohamed Ben Abdellah University. Pursuing her passion for advanced technologies, she earned a Master of Science in Microelectronics, Signals, and Systems from the same institution in 2021. Currently, she is undertaking her doctoral studies at the Computer Science, Signal, Automation, and Cognitivism Laboratory at the Faculty of Sciences in Fez, Morocco. Her academic journey reflects a consistent focus on mastering and innovating in renewable energy systems, particularly wind energy. Yattou’s rigorous training equips her to address complex challenges in energy conversion, modeling, and control systems, blending theoretical and practical approaches to advance sustainable energy solutions.

work Experience

Yattou EL FADILI has extensive experience in renewable energy systems, particularly in wind turbine modeling and control. As a Doctoral Student at the Computer Science, Signal, Automation, and Cognitivism Laboratory, she has contributed to developing innovative control strategies, including sliding mode control, genetic algorithms, and Lyapunov stability theory. She has presented her findings at international conferences such as the International Conference on Intelligent Computing in Data Sciences and the International Conference on Circuit, Systems, and Communication. Yattou’s research publications demonstrate her ability to combine theoretical rigor with practical applications. She is also proficient in designing state-feedback controllers for uncertain systems and optimizing energy systems using fractional calculus. Her collaborative work with peers in multidisciplinary teams has further enriched her expertise in renewable energy and control systems.

Awards and honors

While specific awards and honors are not listed in her profile, Yattou EL FADILI’s contributions to renewable energy research and robust control systems have been recognized through invitations to present at esteemed international conferences. Her papers have been published in high-impact journals, reflecting the academic and professional community’s acknowledgment of her innovative work. Her studies on advanced control strategies for wind turbines, robust state-feedback controllers, and Lyapunov stability approaches have established her as a rising researcher in the field of renewable energy systems. Yattou’s proactive engagement in multidisciplinary collaborations highlights her potential for future accolades in both academia and industry.

Research Focus

Yattou EL FADILI’s research centers on renewable energy, with a strong emphasis on wind turbine control and energy conversion systems. Her work explores the modeling, design, and optimization of controllers using advanced techniques such as sliding mode control, fractional calculus, and Lyapunov stability theory. A significant aspect of her research involves addressing uncertainties in system dynamics through robust state-feedback control. Yattou is also engaged in the design of intelligent systems that incorporate genetic algorithms and neural networks to enhance the efficiency and reliability of wind energy applications. Her interdisciplinary approach integrates physics, electronics, and automation to develop sustainable energy solutions, contributing to global efforts in combating climate change. Her research outputs aim to bridge the gap between theoretical advancements and practical implementation in renewable energy technologies.

Skills

Yattou EL FADILI possesses a diverse skill set spanning renewable energy systems, control theory, and robust system design. Her expertise includes:

Advanced Control Strategies: Sliding mode control, Lyapunov stability theory, fractional calculus, and genetic algorithms.
Renewable Energy Systems: Wind turbine modeling and control, energy conversion systems.
Robust Stability: State-feedback controllers for uncertain systems and singular systems.
Intelligent Systems: Neural networks, optimization techniques for energy efficiency.
Software Proficiency: MATLAB, Simulink, and specialized engineering tools for simulation and control system design.
Interdisciplinary Collaboration: Working with teams across automation, signal processing, and cognitive sciences to innovate energy solutions.

Conclusion

Yattou EL FADILI’s innovative research, academic rigor, and contributions to renewable energy make her a strong contender for the Best Researcher Award. While there is room for broader impact through collaborations and diversification, her achievements are noteworthy and align with the values of the award. Recognizing her work would promote advancements in sustainable energy and inspire emerging researchers globally.

Publications to Noted

Optimal Controller Design for Wind Turbine Using Sliding Sector and Genetic Algorithms
Authors: Y. El Fadili, Y. Berrada, I. Boumhidi
Citation: 4
Year: 2023

Robust Performance of Uncertain System Based on Lyapunov Functions Using Non–Monotonic Terms
Authors: Y. El Fadili, A. Hmamed, B. Boukili, I. Boumhidi
Citation: 4
Year: 2022

Novel Control Strategy for the Global Model of Wind Turbine
Authors: Y. El Fadili, Y. Berrada, I. Boumhidi
Citation: 3
Year: 2024

Improved Sliding Mode Control Law for Wind Power Systems
Authors: Y. El Fadili, Y. Berrada, I. Boumhidi
Citation: 2
Year: 2024

A Novel Combination of Sliding Mode, Fractional Calculus, and Genetic Algorithm to Improve the Performance of a Controller in a Wind Power Application
Authors: Y. El Fadili, B. Youssef, B. Ismail
Citation: 1
Year: 2024

An Advanced Control Law Combining Sliding Mode and Fractional Calculus for Wind Energy Conversion Systems
Authors: Y. El Fadili, Y. Berrada, I. Boumhidi
Citation: 1
Year: 2024

New Design of an Intelligent Electromagnetic Torque Controller Based on Neural Network and Fractional Calculus: Variable-Speed Wind Energy Systems Application
Authors: Y. El Fadili, B. Ismail
Citation: N/A
Year: 2024

Robust State‐Feedback Controller of Uncertain Systems Based on Non‐Monotonic Approach
Authors: Y. El Fadili, B. Boukili, M. N’Diaye, I. Boumhidi
Citation: N/A
Year: 2024

Yattou El Fadili | Renewable energy | Best Researcher Award

Ms.Yattou El Fadili | Renewable energy | Best Researcher Award

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Ms.Yattou El Fadili | Renewable energy | Best Researcher Award

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Research Focus

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Conclusion<img decoding="async" class="an1" draggable="false" src="https://fonts.gstatic.com/s/e/notoemoji/15.1/2705/32.png" alt="✅" data-emoji="✅" aria-label="✅" />

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