Papers
1
Total Citations
16
H-Index
1
About
Bingjie Xu is a researcher in robotics and control systems, with a primary focus on advanced trajectory tracking and motion control for robotic manipulators. Their key contributions lie in developing high-precision control strategies that address the inherent limitations of robotic manipulators in trajectory tracking applications. Notably, Xu introduced a linear-extended-state-observer (LESO)-based prescribed performance controller, a novel approach that significantly enhances tracking accuracy by combining disturbance rejection with performance guarantees. This work, published in 2021, has garnered 16 citations, reflecting its relevance and impact in the field of nonlinear control and robotics. Xu's research is particularly valuable for applications requiring robust and precise robotic motion, such as industrial automation and surgical robotics. By integrating observer-based estimation with prescribed performance constraints, Xu has advanced the state of the art in ensuring both stability and accuracy under uncertain conditions. Their work continues to influence the design of intelligent control systems, making it a key reference for researchers and engineers seeking to improve robotic manipulator performance in real-world environments.
Research Focus
Key Achievements
Top Papers
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