Papers
8
Total Citations
162
H-Index
5
About
Mengshi Zhang is an accomplished robotics and control systems researcher whose work spans rehabilitation robotics, pneumatic muscle actuators, and advanced nonlinear control theory. His research has made significant contributions to the development of intelligent, adaptive control strategies for complex robotic systems, particularly those serving human-centered applications. Zhang's most influential work focuses on pneumatic muscle actuator (PMA)-driven systems, where his adaptive proxy-based robust controller integrated with nonlinear disturbance observation has garnered 53 citations, establishing him as a key voice in handling unpredictable disturbances in physical robotic systems. Equally impactful is his 52-citation contribution to rehabilitation robotics, where he pioneered position-constrained assist-as-needed control methods that balance patient safety with active motor engagement — a critical challenge in neurological injury recovery. Beyond these flagship contributions, Zhang has advanced echo state network-enhanced super-twisting control for gait training exoskeletons, addressed underactuated system challenges through cross-backstepping frameworks, and developed musculoskeletal model-driven impedance control strategies. His growing body of work in neuro-fuzzy personalized rehabilitation control reflects a forward-looking commitment to patient-adaptive therapy. With over 160 cumulative citations and publications spanning 2019 to 2025, Zhang represents an emerging yet already impactful force in intelligent rehabilitation and robust robotic control research.
Research Focus
Key Achievements
Top Papers
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- 5Adaptive Super-Twisting Control for Mobile Wheeled Inverted Pendulum Systems10 citations · 2019
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- 8Robust and Intelligent Control of a Typical Underactuated Robot2 citations · 2023