Zebin Yang
Papers
1
Total Citations
5
H-Index
1
About
Zebin Yang is a researcher advancing the control and stability of robotic actuation systems, with a primary focus on model predictive control (MPC) for flexible joint permanent magnet synchronous motors (FJ-PMSMs). His most-cited work, "Model Predictive Control of Robot Flexible Joint Motor Based on Lyapunov Prediction Model" (2025, 5 citations), addresses a critical challenge in robotics: the parameter sensitivity of flexible joints when using candidate voltage vector strategies. Yang proposed an adaptive method grounded in the Lyapunov function predictive model, which enhances robustness and stability by integrating finite control set MPC with Lyapunov-based stability guarantees. This contribution is particularly significant for improving the precision and reliability of robot manipulators in dynamic environments. Though early in his citation trajectory, his work demonstrates a clear impact on the intersection of control theory and practical robotics. Yang’s research is especially relevant for engineers and researchers developing high-performance, sensorless motor control systems, and his adaptive Lyapunov approach offers a promising pathway toward more resilient and efficient robotic actuation.
Research Focus
Key Achievements
Top Papers
- 1