Papers
18
Total Citations
912
H-Index
12
About
Longbin Zhang is a leading researcher at the intersection of robotics, human-machine interaction, and intelligent control systems. His work primarily focuses on developing advanced control strategies for robotic systems—including exoskeletons, wheel-legged robots, and variable stiffness actuators—with a strong emphasis on human-in-the-loop and brain-machine interfaces. Zhang’s major contributions include pioneering adaptive neural network and fuzzy approximation-based controllers that enable robust trajectory tracking and safe physical interaction under uncertain dynamics. His highly cited papers, such as those on adaptive neural network variable stiffness control (138 citations) and neural fuzzy enhanced tracking for wheel-legged robots (138 citations), demonstrate his impact in addressing nonlinear control challenges. Notably, his research on human-in-the-loop exoskeleton control (132 citations) and brain-machine interface teleoperation (120 citations) has advanced assistive robotics for rehabilitation and dynamic walking. With over 850 total citations across his top works, Zhang has also contributed to EMG-driven torque estimation and model-free tool calibration, earning recognition for integrating neural networks, disturbance observers, and visual compressive sensing into practical robotic systems. His work continues to shape the future of safe, intelligent, and human-centric robotics.
Research Focus
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Top Papers
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