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About

Mohamed Boukens is a researcher specializing in intelligent control systems, robotics, and autonomous navigation, with a particular focus on developing advanced control strategies for mobile robots and robotic manipulators. His work sits at the intersection of neural networks, fuzzy logic, and optimization algorithms, contributing innovative solutions to longstanding challenges in trajectory tracking and motion control. Boukens made a significant impact with his 2017 paper on robust adaptive neural network-based trajectory tracking for nonholonomic electrically driven mobile robots, which has garnered 89 citations and stands as his most influential contribution. This work, alongside his 2016 study on intelligent optimal neural network-based tracking controllers (49 citations), established him as a leading voice in data-driven approaches to mobile robot control. His 2018 research on self-tuning motion controllers introduced a novel algorithm combining ant colony optimization with fuzzy systems, achieving high-precision tracking without costly real-time trial-and-error tuning — earning 36 citations. Earlier work on PD with fuzzy compensator control for robot manipulators demonstrated his long-standing commitment to bridging classical control theory with intelligent computing. Collectively, Boukens' research offers practical, high-performance solutions for real-world robotic systems.