Mohamed S. Mohamed

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About

Mohamed S. Mohamed is a researcher specializing in autonomous mobile robotics, intelligent control systems, and computational intelligence-based optimization. His work centers on solving one of robotics' most persistent challenges: accurate trajectory tracking for differential drive mobile robots, systems that underpin a wide range of real-world autonomous applications from warehouse automation to service robotics. Mohamed's most notable contribution is his development of a Proportional-Integral-Derivative Neural Network (PID NN) controller, which elegantly bridges classical control theory with modern machine learning by embedding neural network principles within a conventional PID framework. Optimized using Particle Swarm Optimization (PSO), this approach demonstrated enhanced nonlinear control performance and earned 12 citations since its 2019 publication, reflecting meaningful uptake within the robotics control community. Complementing this work, he also explored Interval Type-2 Fuzzy Logic controllers — a sophisticated uncertainty-handling technique — as an alternative intelligent control strategy for mobile robot motion, further broadening the toolkit available to robotics engineers. Through these contributions, Mohamed has established himself as a thoughtful innovator in the intersection of soft computing and robotic control, offering practical, hybrid solutions to complex nonlinear problems that continue to inspire follow-on research in intelligent autonomous systems.