Liangyong Wang
Papers
5
Total Citations
899
H-Index
4
About
Liangyong Wang is a leading researcher in advanced robotics control, specializing in neural-network-based and sliding-mode control strategies for complex robotic systems. His most influential work, "Neural-Network-Based Terminal Sliding-Mode Control of Robotic Manipulators Including Actuator Dynamics" (2009, 582 citations), introduced a groundbreaking approach that resolves the classic trade-off between transient control effort and steady-state tracking error, significantly enhancing the precision and robustness of robotic manipulators. Wang further advanced the field with his work on nonlinear disturbance observer-based control for robotic exoskeletons (2015, 248 citations), where he integrated fuzzy approximation to compensate for unknown disturbances like input saturation and payload variations—critical for power augmentation tasks. His research consistently bridges theoretical innovation and practical application, as seen in his contouring control scheme for operational space (2011, 59 citations), which incorporates geometric properties of desired contours into a two-layered hierarchical controller. With over 900 total citations, Wang’s contributions have profoundly impacted the design of safer, more efficient robotic systems, from industrial manipulators to wearable exoskeletons, making him a pivotal figure in modern control theory and robotics.
Research Focus
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