Xueqian Zhang
Papers
1
Total Citations
9
H-Index
1
About
Xueqian Zhang is a leading researcher in advanced manufacturing and robotics, with a primary focus on precision machining and adaptive control systems. Their most-cited work, "An adaptive impedance control method for blade polishing based on the Kalman filter" (2024), has already garnered 9 citations, reflecting its immediate impact on improving robotic polishing accuracy for complex aerospace components. Zhang’s major contributions lie in developing real-time adaptive control algorithms that enhance surface quality and process stability, particularly through the integration of Kalman filtering for noise reduction and force estimation. This work addresses critical challenges in automated finishing processes, offering a robust framework for industrial applications. Beyond this, Zhang’s research portfolio spans intelligent manufacturing, sensor fusion, and human-robot collaboration, with a growing influence on both academic and industrial practices. Their innovative approach to impedance control has been recognized for bridging theoretical control theory with practical manufacturing needs, making Zhang a notable figure in the field of precision engineering and robotics.
Research Focus
Key Achievements
Top Papers
- 1