Papers
8
Total Citations
175
H-Index
6
About
Gaowei Zhang is a leading researcher in the field of robotic exoskeletons and human–robot interaction, with a focus on advanced control strategies that enhance safety, precision, and adaptability. His work centers on developing robust sliding mode control, disturbance observers, and iterative learning methods to manage the complex dynamics of wearable robots. Zhang’s major contributions include the design of periodic event-triggered sliding mode control for lower-limb exoskeletons, which optimizes human–robot cooperation while reducing computational load, and the creation of finite-time disturbance observers for upper-limb exoskeletons that ensure stability under system uncertainties. His most-cited paper (59 citations) exemplifies his impact, while his broader portfolio—spanning command filter backstepping, fixed-time control, and prescribed performance techniques—has garnered over 170 citations. Notably, Zhang has addressed non-repetitive tasks in rehabilitation and robot-assisted bathing, pushing the boundaries of practical exoskeleton deployment. His recent work on control barrier functions for autonomous mobile robots further demonstrates his versatility. Zhang’s research is essential reading for anyone interested in the intersection of nonlinear control theory and assistive robotics.
Research Focus
Key Achievements
Top Papers
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- 4Command Filter Backstepping Sliding Model Control for Lower‐Limb Exoskeleton17 citations · 2017
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