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About

Omar Mohamed Gad is an emerging robotics and control systems researcher whose work spans advanced robot control, autonomous systems, and intelligent optimization techniques. His research focuses on three primary areas: self-balancing robotic platforms, flexible joint manipulators, and the development of sophisticated control strategies including sliding mode control, fractional PID, and fuzzy logic-based approaches. Gad's most recognized contribution involves the design and control of Two-Wheeled Self-Balancing Robots, demonstrating practical implementation using MATLAB and Arduino IDE, earning 12 citations since 2022. His work on rotary flexible joint robots has been particularly prolific, addressing the inherent challenges of nonlinear, underactuated systems through innovative approaches such as fractional PID with prescribed performance functions and adaptive fuzzy Internal Model Control, each garnering 11 and 6 citations respectively. His 2024 study on optimized Power Rate Sliding Mode Control, leveraging genetic algorithms for robot manipulators, highlights his integration of evolutionary computation into control system design. Together, his publications reflect a commitment to solving real-world robotics challenges — from warehouse automation to aerospace inspection — through mathematically rigorous and computationally intelligent methods, establishing him as a promising contributor to modern robotics control engineering.