Papers
2
Total Citations
33
H-Index
2
About
Mohamed A.A. Ismail is a rising researcher in mechatronics and aerospace systems, with a focus on sensorless control, fault diagnosis, and the reliability of electromechanical actuators and unmanned aerial vehicles (UAVs). His most cited work, "Simplified Sensorless Torque Estimation Method for Harmonic Drive Based Electro-Mechanical Actuator" (2021, 31 citations), addresses a critical challenge in aerospace and mechatronic applications: how to achieve accurate torque measurements without costly, complex, or unreliable physical torque sensors. By developing a simplified estimation method, Ismail’s research enables enhanced control and monitoring loops, reducing system cost and complexity while maintaining performance. His more recent work, "Offboard Fault Diagnosis for Large UAV Fleets Using Laser Doppler Vibrometer and Deep Extreme Learning" (2025, 2 citations), pushes into the frontier of smart agricultural robotics and large-scale UAV operations. Here, he proposes a novel approach that replaces traditional vibration and noise-based diagnostics with laser-based remote sensing combined with deep extreme learning, offering a scalable, non-contact solution for fleet-wide fault detection. Ismail’s contributions are particularly impactful for industries seeking to deploy reliable, cost-effective autonomous systems at scale, bridging the gap between theoretical control methods and practical, sensor-light implementations.
Research Focus
Key Achievements
Top Papers
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