Yumei Ma
Papers
1
Total Citations
9
H-Index
1
About
Dr. Yumei Ma is a leading researcher in intelligent robotic control systems, with a primary focus on adaptive control, neural network-based estimation, and disturbance rejection for uncertain robotic manipulators. Her most-cited work, "Adaptive neural network command filtered backstepping impedance control for uncertain robotic manipulators with disturbance observer" (2021, 9 citations), introduces a pioneering framework that integrates adaptive neural networks to estimate uncertain dynamics while employing a disturbance observer to enhance robustness. This approach addresses critical challenges in real-world robotics, such as handling unknown system parameters and external disturbances, enabling safer and more precise human-robot interaction through impedance control. Dr. Ma’s contributions are particularly notable for advancing command filtered backstepping techniques, which simplify controller design without sacrificing stability or performance. Her work has garnered attention for its practical applicability in industrial and service robotics, laying groundwork for more adaptive and resilient autonomous systems. Through these innovations, Dr. Ma continues to shape the future of intelligent robotic control, offering elegant solutions to complex, nonlinear system challenges.
Research Focus
Key Achievements
Top Papers
- 1