Nezar M. Alyazidi
Papers
6
Total Citations
64
H-Index
4
About
Nezar M. Alyazidi is an emerging researcher specializing in advanced control systems, robotics, and intelligent optimization techniques. His work sits at the intersection of fractional-order control theory, metaheuristic optimization, and robotic manipulation, with a growing focus on fault-tolerant and cyber-secure autonomous systems. Alyazidi's most impactful contributions involve the application of fractional-order PID (FO-PID) controllers to nonlinear robotic manipulator systems, optimized through evolutionary algorithms such as improved particle swarm optimization (IPSO) and genetic algorithms (GA). His 2024 studies comparing FO-PID against conventional PID controllers have rapidly gained traction, accumulating 24 and 23 citations respectively, reflecting strong community interest in precision robotic control. His 2025 work on fractional-order sliding mode control (FOSMC) further demonstrates his commitment to addressing real-world disturbances and system uncertainties with mathematically rigorous solutions. Beyond manipulator control, Alyazidi has extended his expertise to multi-robot formation control with fault-tolerance capabilities and cybersecurity in teleoperation systems, developing a deep learning-based attack detector for bilateral teleoperation networks. Together, these contributions position him as a versatile and forward-thinking researcher making meaningful strides in robust, intelligent robotics and control engineering.
Research Focus
Key Achievements
Top Papers
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- 4Deep Learning-based Attack Detector for Bilateral Teleoperation Systems4 citations · 2022
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