Dejun Mu

Papers

Total Citations

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About

Dejun Mu is a robotics and control systems researcher whose work focuses on advanced friction compensation and adaptive control strategies for robotic manipulators. His most-cited paper, "Observer based friction compensation in robot control" (2005), introduces a novel approach that leverages the LuGre friction model to address the persistent challenge of friction in low-speed and precision robot operations. By developing an observer to estimate undetectable presliding displacement and low-speed dynamics, Mu enables feed-forward friction compensation that significantly improves tracking accuracy. His methodology integrates adaptive parameter identification for both friction and linearized robot dynamics, combined with a robust PD + feed-forward control framework. While his citation count (5 citations for this seminal work) reflects a focused, niche contribution, the impact lies in its practical utility for engineers tackling real-world friction effects in robotic systems. Mu’s work exemplifies how theoretical modeling and observer-based estimation can bridge the gap between complex friction phenomena and implementable control solutions, making his research valuable for students and practitioners in robotics, mechatronics, and precision motion control.