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About

Yufei Qi’s research centers on advanced control systems for robotic manipulators, with a particular focus on trajectory tracking, human-robot cooperation, and disturbance rejection in industrial automation. Their most notable contribution is the development of a repetitive control scheme for robotic manipulators using improved cubic B-spline functions, which enhances precision in periodic tasks. This work, published in 2021, has garnered 8 citations and demonstrates a novel integration of iterative control with disturbance observers. Qi further advanced the field with a 2022 study on a modified supertwisting sliding mode controller, incorporating fuzzy adaptive logic to achieve rapid convergence and robust performance in human-robot collaborative assembly lines—a critical innovation for modern manufacturing safety and efficiency. With a career spanning from early vision-based localization analysis (2013) to cutting-edge sliding mode techniques, Qi’s research addresses real-world challenges in industrial robotics, offering practical solutions for precision and adaptability. Their work, though still building citation momentum, reflects a focused trajectory toward making robotic systems more reliable and interactive in dynamic environments.