Rim Jallouli Khlif

University of Sfax

Papers

4

Total Citations

30

H-Index

4

About

Rim Jallouli Khlif is an emerging researcher specializing in advanced control systems, with a particular focus on fractional-order control, sliding mode control, and adaptive strategies applied to robotic systems. Her work sits at the intersection of control theory and robotics, addressing critical challenges such as trajectory tracking precision, system robustness, and energy efficiency in complex polyarticulated and rehabilitation robotic platforms. Among her most notable contributions is the development of an L₁ adaptive fractional control framework optimized through genetic algorithms, which has garnered 10 citations since its 2021 publication. She has further advanced the field through her Fractional-Order Sliding Mode Control (FO-SMC) strategies, demonstrating improved reliability and performance in robotic manipulators, and by integrating fuzzy logic for intelligent parameter tuning to balance energy consumption with transient response quality. Her more recent work on rehabilitation robots — specifically lower-limb exoskeletons — highlights her commitment to translating rigorous control theory into meaningful healthcare applications. With a growing citation record and a research agenda spanning optimization, intelligent control, and biomedical robotics, Rim Jallouli Khlif represents a promising voice in modern control engineering whose contributions are increasingly recognized by the international research community.

Research Focus

Key Achievements

4
H-Index
4
Papers
30
Total Citations
8
Avg Citations/Paper
🏆 Most Cited Paper
<a:math xmlns:a="http://www.w3.org/1998/Math/MathML" id="M1"> <a:msub> <a:mrow> <a:mi>L</a:mi> </a:mrow> <a:mrow> <a:mn>1</a:mn> </a:mrow> </a:msub> </a:math> Adaptive Fractional Control Optimized by Genetic Algorithms with Application to Polyarticulated Robotic Systems
10 citations · 2021
📈 Most Prolific Year: 2024 (2 Papers)
🤝 Key Collaborators: 7
🏛 Institutions: University of Sfax

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 17 days ago