Rehab Yahia
Papers
1
Total Citations
4
H-Index
1
About
Rehab Yahia is a control systems researcher whose work focuses on the robust control of robotic manipulators, particularly in the presence of unknown external disturbances. Her key research areas include nonlinear observer design, state estimation, and linear matrix inequality (LMI)-based control synthesis. Her most-cited paper, "Robust Control of a Robotic Manipulator Using LMI-Based High-Gain State and Disturbance Observers" (2018), introduces a dual-observer framework that combines a high-gain state observer with a nonlinear disturbance observer to stabilize n-DOF manipulator robots. This approach enables precise trajectory tracking and disturbance rejection without requiring full-state measurement, addressing a critical challenge in industrial and service robotics. With 4 citations, this work has contributed to advancing robust control strategies for uncertain robotic systems. Yahia’s methodology is particularly notable for its practical applicability, offering a systematic LMI-based design that ensures stability and performance. Her research bridges theoretical control theory and real-world robotic applications, making her work valuable for engineers and researchers developing resilient autonomous systems.
Research Focus
Key Achievements
Top Papers
- 1