Xingzhe Han
Papers
2
Total Citations
8
H-Index
2
About
Xingzhe Han is a rising researcher in nonlinear control theory and autonomous robotics, with a focus on safe and adaptive dynamic systems. His work centers on developing robust adaptive safety control frameworks for uncertain nonlinear systems, particularly addressing the challenge of ensuring stability and safety in real-time robotic applications. Han introduced the novel concepts of robust adaptive control Lyapunov functions (RACLF) and robust adaptive control barrier functions (RACBF), which provide a theoretical foundation for integrating adaptation with safety guarantees in the presence of parametric uncertainties. His two most-cited papers, both published in 2024 and 2025, each with 4 citations, apply these frameworks to differential robots, demonstrating practical coverage control and dynamic safety enforcement. Though early in his career, Han’s contributions are notable for bridging rigorous control theory with deployable robotic systems, offering a pathway to safer autonomous navigation in uncertain environments. His work is particularly relevant for students and researchers in nonlinear control, adaptive systems, and robotics, promising to influence future developments in safe autonomy.
Research Focus
Key Achievements
Top Papers
- 1
- 2