Papers
29
Total Citations
917
H-Index
15
About
Dr. Tairen Sun is a leading authority in robot control systems, specializing in impedance control, adaptive neural networks, and sliding-mode disturbance observers. His seminal work, "Neural network-based sliding mode adaptive control for robot manipulators" (249 citations), established a robust framework for handling uncertain dynamics in robotic systems. Dr. Sun’s major contributions include developing stability-guaranteed variable impedance control and composite learning-enhanced impedance control, which ensure precise robot-environment interaction even under modeling uncertainties. His research on semiglobal exponential control using sliding-mode disturbance observers (71 citations) and robust adaptive control for environmental boundary tracking by mobile robots (70 citations) has significantly advanced autonomous navigation and rehabilitation robotics. Notably, his 2022 work on spatial repetitive impedance learning control for robot-assisted rehabilitation demonstrates practical applications in human-robot collaboration. With over 800 total citations across his top papers, Dr. Sun’s innovations in disturbance rejection and adaptive learning continue to shape modern robotics, offering reliable solutions for complex, real-world tasks.
Research Focus
Key Achievements
Top Papers
- 1Neural network-based sliding mode adaptive control for robot manipulators249 citations · 2011
- 2Composite Learning Enhanced Robot Impedance Control82 citations · 2019
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