Papers
10
Total Citations
168
H-Index
7
About
Abbas Chatraei is a control systems researcher whose work sits at the intersection of robotics, intelligent control, and nonlinear systems theory. His research primarily focuses on advanced control strategies for robot manipulators and wheeled mobile robots, with particular expertise in adaptive control, neural network-based observers, output feedback methods, and multi-agent formation control. Among his most impactful contributions is a prescribed performance-based neural adaptive PID² controller for robot manipulators that elegantly handles model uncertainties without requiring velocity, acceleration, or current measurements — a practically significant achievement that has garnered 66 citations since its 2020 publication. His passivity-based output feedback controllers for Euler-Lagrange systems with input saturation, developed as early as 2012–2015, established a foundational thread running throughout his career, later validated experimentally on the SCARA IBM 7547 industrial robot. More recently, Chatraei has extended this expertise into multi-robot coordination, publishing influential work on leader-follower formation control with limited field-of-view constraints (32 citations). His 2024 reinforcement learning-based saturated PID controller signals a forward-looking integration of data-driven techniques with classical control theory, reflecting a research trajectory that consistently bridges rigorous theoretical development with real-world experimental validation.
Research Focus
Key Achievements
Top Papers
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- 4Global Optimal Feedback‐Linearizing Control of Robot Manipulators12 citations · 2012
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