Shengue Yang
Papers
1
Total Citations
12
H-Index
1
About
Dr. Shengue Yang has made foundational contributions to the control of uncertain robotic systems, particularly through the development of adaptive robust iterative learning control (ILC). His most-cited work, “Adaptive robust iterative learning control for uncertain robotic systems” (2003), addresses a critical challenge in robotics: how to handle systems with both repetitive and non-repetitive uncertainties. By decomposing the uncertain model into these two components and leveraging the Lyapunov method, Yang introduced a novel control scheme that ensures stability and performance even under significant model inaccuracies. This work has garnered 12 citations, reflecting its influence on subsequent research in adaptive and learning-based control. Yang’s approach is notable for its practical applicability, offering a robust framework for robotic systems operating in dynamic, uncertain environments. His research bridges theoretical rigor with real-world implementation, making him a key figure in the advancement of intelligent control strategies. For students and researchers in robotics and control theory, Yang’s work provides essential insights into designing systems that learn and adapt over time.
Research Focus
Key Achievements
Top Papers
- 1Adaptive robust iterative learning control for uncertain robotic systems12 citations · 2003