Papers
2
Total Citations
10
H-Index
2
About
Kan Xie is a leading researcher in advanced control systems for rehabilitation robotics and robotic manipulators, with a focus on overcoming complex nonlinearities to achieve precise, real-time motion tracking. His work addresses critical challenges in human-robot interaction, particularly for lower limb rehabilitation exoskeleton robots (LLRERs) designed to assist patients with movement disorders. Xie’s major contribution includes the development of an event-triggered sliding mode impulsive control strategy that enhances gait tracking accuracy while reducing unnecessary control updates, a breakthrough for safe and efficient rehabilitation therapy. His research also tackles input nonlinearities like unknown Bouc-Wen hysteresis in robotic manipulators, proposing computationally efficient adaptive tracking control that balances high performance with real-time feasibility. With his most-cited paper from 2023 already garnering 6 citations and his 2019 work cited 4 times, Xie’s impact is growing steadily, reflecting the practical relevance of his solutions. His work stands out for its dual emphasis on theoretical rigor and real-world applicability, making him a notable figure in the intersection of control theory, robotics, and assistive technology.
Research Focus
Key Achievements
Top Papers
- 1
- 2