Zexuan Li
Papers
1
Total Citations
24
H-Index
1
About
Zexuan Li is a leading researcher in advanced control systems, with a focus on intelligent robotics and nonlinear dynamics. Their most influential work, "Nonlinear Nonsingular Fast Terminal Sliding Mode Control Using Deep Deterministic Policy Gradient" (2021, 24 citations), addresses persistent challenges in industrial robot control—specifically, the trade-off between chattering suppression and tracking accuracy. By integrating deep reinforcement learning (Deep Deterministic Policy Gradient) with nonsingular fast terminal sliding mode control, Li pioneered a hybrid approach that enhances response speed while mitigating the chattering that degrades precision. This contribution bridges classical control theory with modern AI, offering a robust framework for high-performance robotic manipulation. Li’s research is distinguished by its practical impact on automation, where their methods improve the reliability and efficiency of industrial robots in real-world tasks. With growing recognition in the control engineering community, Li continues to push the boundaries of adaptive and learning-based control, making their work essential reading for students and researchers seeking to advance intelligent mechatronic systems.
Research Focus
Key Achievements
Top Papers
- 1