Shoudao Huang
Papers
2
Total Citations
5
H-Index
2
About
Shoudao Huang has made significant contributions to advanced control systems for industrial robotics and permanent magnet synchronous motor (PMSM) drives. His research focuses on sensorless motor control, adaptive sliding mode control, and neural network-based approaches for robotic manipulators. In his notable 2021 work on de-icing industrial robot manipulators, Huang developed an innovative adaptive robust backstepping sliding mode control integrating neural networks with dead zone compensation, achieving enhanced trajectory tracking and disturbance rejection. This work has garnered 3 citations, demonstrating its emerging impact in industrial automation. Earlier, in 2015, Huang proposed an improved method for initial rotor position estimation and magnetic polarity identification in surface PMSM systems, addressing critical challenges in sensorless motor start-up control. This contribution, with 2 citations, helps reduce system costs while improving reliability by eliminating position sensors. Huang's work bridges theoretical control advances with practical industrial applications, particularly in robotics and electric drives. His research continues to influence the development of more robust, sensorless control strategies for modern manufacturing and automation systems.
Research Focus
Key Achievements
Top Papers
- 1
- 2