Papers

5

Total Citations

22

H-Index

3

About

Shuyang Liu is a leading researcher in advanced robotics, specializing in the control of rigid-flexible manipulators and distributed parameter systems. His work addresses critical challenges in robotic manipulation, particularly for systems where flexibility and actuator constraints complicate precision control. Liu’s most-cited paper (2022, 9 citations) introduces an observer-based independent joint control scheme for coupled rigid-flexible manipulators, tackling actuator saturation and external disturbances using a distributed parameter model. He further advanced the field with an adaptive boundary control strategy (2023, 5 citations) that handles concurrent actuator and sensor failures under multiple constraints, and an infinite-dimensional observer-based approach (2022, 4 citations) for flexible beam manipulation by multi-link robots. More recently, Liu has explored hierarchical imitation learning for robotic skill acquisition (2024, 2 citations), bridging control theory with cognitive robotics. His early work on nonlinear direct joint control for manipulators handling flexible payloads (2019, 2 citations) established his foundational expertise. With a focus on mathematically rigorous distributed parameter models, Liu’s contributions enable safer, more reliable robotic systems in manufacturing, space exploration, and service robotics, making him a key figure in modern robotic control theory.

Research Focus

Key Achievements

3
H-Index
5
Papers
22
Total Citations
4
Avg Citations/Paper
🏆 Most Cited Paper
Observer-based independent joint control for a coupled rigid-flexible manipulator with actuator saturation based on distributed parameter model
9 citations · 2022
📈 Most Prolific Year: 2022 (2 Papers)
🤝 Key Collaborators: 12
🏛 Institutions: Changchun University of Technology, Nanjing University

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago