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About

Mahmoud Mohamed is an emerging researcher specializing in advanced control systems, robotic stabilization, and intelligent controller design. His work centers on the Robogymnast — a sophisticated triple-link robotic system that models a human gymnast swinging on a high bar — representing one of the most challenging control problems in robotics due to its inherent nonlinearity and high complexity as a triple-inverted pendulum. Mohamed's primary contributions lie in developing, comparing, and optimizing a range of controllers for multi-link robotic systems, including Linear Quadratic Regulators (LQR), PID controllers, Proportional Derivative (PD) controllers, and hybrid Fuzzy Logic approaches. His research systematically evaluates how conventional and intelligent control strategies perform under demanding stability conditions, with his hybrid Fuzzy-LQR frameworks demonstrating notable improvements in system performance. His most recent work pushes further by incorporating optimization algorithms to enhance Fuzzy-LQR controller efficiency. Publishing prolifically in 2022–2023, Mohamed has accumulated over 32 citations across five focused studies, signaling growing recognition within the robotics and control engineering community. His research provides valuable frameworks for students and engineers working on complex dynamic systems, advanced stabilization techniques, and the intersection of classical and computational intelligence-based control methodologies.