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About

Arash Khatamianfar’s research lies at the intersection of robotics and advanced control systems, with a particular focus on industrial automation and precision motion control. His work primarily addresses the complex challenges of overhead crane automation, where he has pioneered novel discrete-time control strategies that simultaneously achieve robust trajectory tracking and effective load swing suppression. Drawing inspiration from independent joint control techniques in robot manipulators, Khatamianfar developed a new modeling approach that treats crane actuators as the primary plant, enabling more accurate and reliable servo control in real-world industrial settings. His contributions extend to system identification and friction modeling, providing essential frameworks for parameter estimation that improve control accuracy in mechanical systems. With his most cited paper, “Task space control of a welding robot using a fuzzy coordinator” (16 citations), he has also demonstrated expertise in robotic manipulation and fuzzy logic coordination. Through a series of methodical studies published between 2010 and 2015, Khatamianfar has established a coherent body of work that bridges theoretical control design with practical implementation, offering valuable solutions for industries reliant on precise material handling and automated welding processes.