Papers
8
Total Citations
131
H-Index
7
About
Yiyong Sun is a leading researcher in intelligent control systems, with a primary focus on the balance and trajectory control of underactuated bicycle robots and single-track two-wheeled robots. His work addresses fundamental challenges in nonlinear dynamics, including time-varying velocity, ramp jumping, and uncertainty handling. Sun’s most-cited paper (37 citations) introduces a learning-based Gaussian process framework for trajectory tracking and balance control, moving beyond exact dynamic modeling to manage system uncertainties. He has also pioneered fuzzy multi-objective dynamic programming and continuous reinforcement learning approaches for agile robot maneuvers. Beyond wheeled robots, Sun contributes to fault diagnosis in control moment gyroscopes using attention-enhanced CNNs (21 citations) and develops sliding mode observers for coupled disturbance reconstruction in nonlinear systems. His research extends to segmented hybrid motion-force control for hyper-redundant space manipulators, demonstrating versatility across terrestrial and aerospace applications. With over 130 cumulative citations, Sun’s work is distinguished by its integration of learning-based methods with classical control theory, offering practical solutions for complex, real-world robotic systems.
Research Focus
Key Achievements
Top Papers
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- 6Polynomial Controller for Bicycle Robot based on Nonlinear Descriptor System11 citations · 2020
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