Papers
33
Total Citations
861
H-Index
17
About
Khoshnam Shojaei is a prominent control systems researcher whose work centers on the design of intelligent and adaptive controllers for mobile robotic systems, with particular expertise in wheeled mobile robots, robot manipulators, and multi-agent formation control. His research consistently tackles real-world challenges such as parametric uncertainty, nonholonomic constraints, actuator saturation, and the absence of velocity measurements — limitations that make practical robot deployment notoriously difficult. Shojaei's early contributions established foundational adaptive control frameworks for differential-drive mobile robots, earning over 90 citations each for two landmark 2010 papers. His dynamic surface control and output feedback approaches further demonstrated his ability to bridge theoretical rigor with implementable solutions. Notably, he extended these methods to multi-robot formation control, developing neural adaptive schemes for car-like and general-type wheeled mobile robots that accommodate real-world sensor limitations. His 2020 work on prescribed performance neural adaptive PID control for robot manipulators — accumulating 66 citations — reflects his growing focus on guaranteed transient behavior and observer-based architectures. More recently, his foray into agricultural robotics, including coordinated control of autonomous tractors and combine harvesters, signals a compelling expansion toward field robotics applications. With a cumulative citation count exceeding 550, Shojaei's body of work represents a sustained and impactful contribution to intelligent robotic control.
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