Shuaiying Wang
Papers
1
Total Citations
3
H-Index
1
About
Shuaiying Wang is a researcher specializing in control systems and robotics, with a particular focus on model predictive control (MPC) and its application to autonomous mobile systems. Their most notable contribution is the development of a nonlinear model predictive tracking control scheme for wheeled mobile robots, which employs a polytopic linear differential inclusion (PLDI)-based method to enhance trajectory tracking performance. This work, published in 2020, introduces a novel approach to obtaining a suitable terminal penalty term, addressing key challenges in stability and constraint satisfaction for robotic motion control. While still early in their career, with the cited paper accumulating 3 citations, Wang’s research demonstrates a strong foundation in advanced control theory and its practical implementation. Their work is particularly relevant to the growing field of autonomous navigation, where precise trajectory tracking is critical for applications such as warehouse logistics, service robotics, and autonomous driving. Wang’s contributions offer valuable insights for researchers and students exploring robust control strategies for wheeled mobile robots operating in dynamic environments.
Research Focus
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Top Papers
- 1