Papers
2
Total Citations
16
H-Index
2
About
Yesong Li is a researcher focused on advanced control systems and fault diagnosis in electromechanical and robotic systems. Their primary research areas include internal model control for robotic drive systems with elastic joints, and mechanical fault diagnosis using self-sensing motor drives. Li’s most cited work, "Modified Internal Model Control Scheme for the Drive Part with Elastic Joints in Robotic System" (2014, 11 citations), introduces a refined control strategy that enhances stability and precision in robotic manipulators, addressing critical challenges in industrial automation. Their 2021 review, "Mechanical Fault Diagnosis Based on Self-Sensing Motor Drive: Review and Key Issues" (5 citations), synthesizes emerging techniques for condition monitoring in CNC machines and industrial robots, emphasizing how motor drive signals can replace traditional vibration sensors to improve system reliability and safety. This work highlights Li’s contribution to developing cost-effective, integrated diagnostic methods for key manufacturing equipment. While their citation counts are modest, Li’s research offers practical insights for improving the security and efficiency of automated systems, making their work relevant to engineers and researchers in robotics and industrial control.
Research Focus
Key Achievements
Top Papers
- 1
- 2