Papers

7

Total Citations

110

H-Index

5

About

Wenkang Xu’s research lies at the intersection of robotics, control theory, and biomedical engineering, with a primary focus on developing intelligent control systems for robotic-assisted rehabilitation and human-robot interaction. His most influential work addresses the critical challenge of muscle fatigue in upper limb stroke rehabilitation, where he pioneered iterative learning control (ILC) frameworks that adapt assistive stimulation in real-time—a contribution cited over 50 times. Xu also made significant advances in time-varying force control for robot manipulators, introducing neural-network-based approaches and improved position-based impedance control (IPBIC) to handle uncertainties in the manipulator–environment system. These contributions, totaling nearly 100 citations, provide robust solutions for precise force tracking in dynamic settings. Beyond rehabilitation, Xu has explored transformable robotics, designing a double-body car-snake hybrid robot for autonomous inspection. His work is notable for bridging theoretical control methods with practical applications in healthcare and field robotics, offering students and researchers a compelling model of how adaptive control can enhance robotic performance in uncertain, real-world environments.

Research Focus

Key Achievements

5
H-Index
7
Papers
110
Total Citations
16
Avg Citations/Paper
🏆 Most Cited Paper
Iterative learning control for robotic-assisted upper limb stroke rehabilitation in the presence of muscle fatigue
50 citations · 2014
📈 Most Prolific Year: 2014 (3 Papers)
🤝 Key Collaborators: 10
🏛 Institutions: Nanjing University of Science and Technology, Tianjin University

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 15 days ago