Shoulei Ma
Papers
1
Total Citations
212
H-Index
1
About
Shoulei Ma is a leading researcher in advanced control systems, with a primary focus on electro-hydraulic servo systems, adaptive control, and neural network-based methodologies. Their most impactful contribution is the development of a novel adaptive sliding mode controller integrating Radial Basis Function (RBF) neural networks, which significantly enhances the precision and robustness of electro-hydraulic servo systems under uncertain and nonlinear conditions. This work, published in 2022, has already garnered over 212 citations, underscoring its influence in the field of mechatronics and automation. Ma’s research bridges theoretical control design with practical engineering applications, offering solutions that improve system stability and tracking performance. Their work is widely recognized for its innovative fusion of sliding mode control and neural network adaptation, providing a foundation for future advancements in intelligent actuation systems. With a growing citation record and a focus on real-world industrial challenges, Shoulei Ma continues to shape the landscape of adaptive control and servo system optimization.
Research Focus
Key Achievements
Top Papers
- 1