Xunkai Gao
Papers
1
Total Citations
16
H-Index
1
About
Xunkai Gao is a researcher in advanced robotics and nonlinear control systems, with a primary focus on manipulator dynamics and disturbance rejection. His most cited work, "Neural network based dynamic surface integral nonsingular fast terminal sliding mode control for manipulators with disturbance rejection" (2023, 16 citations), introduces a novel control framework that integrates neural networks with sliding mode techniques to enhance the precision and robustness of robotic manipulators under uncertain conditions. This contribution addresses critical challenges in real-time motion control, such as singularity avoidance and chattering reduction, offering a practical solution for high-performance automation. Gao’s research is particularly impactful in applications requiring precise manipulation in the presence of external disturbances, including industrial robotics and autonomous systems. His work has garnered attention for its innovative combination of adaptive neural compensation and dynamic surface control, providing a foundation for future studies in intelligent robotic control. With a growing citation record, Gao is establishing himself as a promising voice in the field of nonlinear control and mechatronics.
Research Focus
Key Achievements
Top Papers
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