Claude Ziad El‐Bayeh
Papers
6
Total Citations
45
H-Index
4
About
Claude Ziad El‐Bayeh is a robotics control researcher whose work focuses on developing advanced control strategies for uncertain robotic systems, including manipulator robots, exoskeletons, biped robots, and quadrotors. His major contributions lie in adaptive and robust control theory, particularly in combining backstepping control with function approximation techniques and neural network estimation to handle unknown dynamics and disturbances. El‐Bayeh has pioneered novel sliding mode control approaches with modified reaching laws that overcome traditional limitations, as demonstrated in his work on upper limb exoskeleton robots. His most cited paper, "Impedance learning control for physical human-robot cooperative interaction" (2021), has garnered 21 citations, highlighting its significance in human-robot collaboration. Other notable works include adaptive backstepping control for manipulator robots and modified fast terminal super-twisting control for uncertain systems. His research addresses critical challenges in tracking performance under parameter variations and unmodeled dynamics, making his contributions valuable for real-world robotic applications where precision and robustness are essential.
Research Focus
Key Achievements
Top Papers
- 1Impedance learning control for physical human-robot cooperative interaction21 citations · 2021
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- 6Backstepping control based on neural network estimation2 citations · 2024