Xinlin Zhang
Papers
8
Total Citations
76
H-Index
5
About
Xinlin Zhang is a leading researcher in soft robotics and intelligent control systems, specializing in pneumatic artificial muscle (PAM)-driven robots. Their work addresses critical challenges in human-robot interaction, focusing on hysteresis compensation, adaptive control, and motion constraints for compliant robotic systems. Zhang’s most cited paper (28 citations) introduces hysteresis compensation-based intelligent control for PAM-driven humanoid manipulators, demonstrating experimental validation of soft actuator adaptability. Another highly influential work (19 citations) develops observer-based adaptive fuzzy event-triggered control for mechatronic systems with time-delay and motion constraints, reducing communication costs while maintaining stability. Recent contributions include disturbance preview-based predictive control (10 citations) and admittance-based fuzzy switching control via nonsingular terminal sliding mode (6 citations), both advancing PAM robot precision. Zhang has also pioneered LSTM-neural-network-enhanced tracking control (5 citations) and supervised learning with preassigned-time performance (4 citations), integrating machine learning with classical control theory. With over 70 total citations across eight recent publications (2022–2025), Zhang’s research consistently pushes boundaries in soft actuator control, offering practical solutions for safer, more efficient human-robot collaboration.
Research Focus
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