Jinlei Wang
Papers
1
Total Citations
4
H-Index
1
About
Dr. Jinlei Wang is a researcher in robotics and control systems, with a primary focus on rehabilitation robotics and iterative learning control (ILC). His most cited work, "Iterative Learning Control of Exponential Variable Gain Based on Initial State Learning for Upper Limb Rehabilitation Robot" (2019), addresses a critical challenge in assistive robotics: achieving precise trajectory tracking for nonlinear upper limb rehabilitation systems. Wang proposed an innovative exponential variable gain D-type ILC law that incorporates initial state learning, significantly improving the convergence speed and tracking accuracy of robotic exoskeletons used in physical therapy. This contribution has garnered 4 citations and represents a meaningful step toward more adaptive and patient-specific rehabilitation protocols. Wang's research sits at the intersection of nonlinear control theory and practical medical robotics, aiming to enhance the autonomy and effectiveness of rehabilitation devices. His work is particularly relevant for researchers developing intelligent assistive technologies that require high-precision motion control over finite time intervals. By integrating variable gain strategies with iterative learning, Wang has helped advance the field of human-robot interaction in clinical settings, offering a foundation for future innovations in adaptive rehabilitation systems.
Research Focus
Key Achievements
Top Papers
- 1