Keyi Xing
Papers
1
Total Citations
9
H-Index
1
About
Keyi Xing is a researcher whose work lies at the intersection of robotics, control systems, and fuzzy logic, with a particular focus on adaptive control strategies for complex mechanical systems. Xing's most cited paper, "Fuzzy Adaptation Algorithms’ Control for Robot Manipulators with Uncertainty Modelling Errors" (2018, 9 citations), introduces a novel fuzzy control scheme that addresses the critical challenge of managing uncertainty in robot manipulator dynamics. By incorporating a single adjustable parameter into the fuzzy logic system, Xing's approach enables more robust control of manipulator systems, treating the robot as a master device that must track a reference model despite nonlinear uncertainties. This work contributes to the broader field of intelligent control by demonstrating how adaptive fuzzy algorithms can compensate for modeling errors without requiring extensive system identification. Xing's research is particularly relevant for applications in industrial automation and advanced robotics, where precise manipulation under uncertain conditions is essential. The paper's citation count reflects its value to researchers working on control theory and robotic systems, establishing Xing as a contributor to the ongoing development of more resilient and adaptive robotic control frameworks.
Research Focus
Key Achievements
Top Papers
- 1