Papers
42
Total Citations
668
H-Index
15
About
Shengchao Zhen is a prominent robotics and control systems researcher whose work spans robotic manipulators, rehabilitation robotics, mobile robots, and dynamic modeling. His research is anchored in developing advanced control frameworks—particularly adaptive robust control, prescribed performance control, and Lyapunov-based methods—that address real-world uncertainties such as friction, modeling errors, and unknown disturbances in complex nonlinear systems. Among his most influential contributions is the application of the Udwadia-Kalaba theory to dynamic modeling and control, producing foundational work cited over 70 times that transformed how constrained multi-body robotic systems are analyzed and controlled. His 2023 paper on prescribed performance adaptive robust control for robotic manipulators has already garnered 79 citations, reflecting strong contemporary relevance. Equally notable is his sustained focus on rehabilitation robotics, with multiple papers addressing lower limb rehabilitation robots under passive training conditions—work carrying meaningful societal impact for assistive technologies. Zhen has also made practical contributions to SCARA robots, humanoid arms, snake robots, and underactuated mobile platforms, consistently bridging theoretical rigor with experimental validation. With a portfolio accumulating over 400 citations across a decade of research, Zhen stands as an influential voice in intelligent and robust robot control design.
Research Focus
Key Achievements
Top Papers
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- 5A novel adaptive robust control approach for underactuated mobile robot41 citations · 2019
- 6A new PD based robust control method for the robot joint module37 citations · 2021
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- 8A Novel Practical Robust Control Inheriting PID for SCARA Robot23 citations · 2020
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