Ming Hui Zheng
Papers
1
Total Citations
7
H-Index
1
About
Ming Hui Zheng is a robotics researcher whose work focuses on the control and trajectory tracking of unconventional mobile systems, particularly spherical robots. His most cited paper, "Trajectory Tracking of a Spherical Robot Based on an RBF Neural Network" (2011, 7 citations), addresses the complex challenge of controlling the BHQ-1 spherical robot. In this work, Zheng proposed a two-tier control strategy: first, a PD controller based on kinematics to generate a desired velocity, and then a PD controller augmented with a Radial Basis Function (RBF) neural network to achieve precise trajectory tracking. This hybrid approach demonstrates his contribution to integrating neural network-based adaptive control with classical control theory for nonlinear, underactuated systems. While his citation count is modest, his research is notable for tackling a niche but challenging problem in mobile robotics—spherical robots, which offer unique advantages in stability and maneuverability but are notoriously difficult to control. Zheng's work provides a foundation for further advancements in intelligent control for non-holonomic robotic platforms.
Research Focus
Key Achievements
Top Papers
- 1Trajectory Tracking of a Spherical Robot Based on an RBF Neural Network7 citations · 2011