Papers
7
Total Citations
104
H-Index
5
About
Ahmed Eltayeb is a robotics and control systems researcher whose work sits at the intersection of advanced control theory, robotic manipulator design, and autonomous systems. His most recognized contribution, a 2018 study on PID and sliding mode control for a two-link robotic manipulator (35 citations), established a foundation for his sustained investigation into robust and adaptive control strategies. Building on this, his 2019 work introduced an adaptive sliding mode controller grounded in Lyapunov stability theory to handle system uncertainties in multi-input, multi-output robotic arms. More recently, Eltayeb has embraced intelligent optimization techniques, publishing comparative analyses of fractional-order PID versus standard PID controllers optimized via genetic algorithms, and introducing an improved particle swarm optimization approach for fractional-order controller tuning — both papers accumulating significant early citations in 2024. His research portfolio also spans soft robotics, where he proposed a novel three-parallel soft muscle actuator validated through finite element analysis, delta parallel robot kinematics, and multi-domain robot swarm systems for industrial mapping. With a cumulative citation count exceeding 100, Eltayeb's career reflects a productive trajectory bridging classical control theory with emerging intelligent and biologically inspired robotics applications.
Research Focus
Key Achievements
Top Papers
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- 4Adaptive sliding mode control design for the 2-DOF robot arm manipulators10 citations · 2019
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- 7Kinematic Analysis of Delta Parallel Robot: Simulation Study2 citations · 2021