Xinglei Xu
Papers
1
Total Citations
8
H-Index
1
About
Xinglei Xu is a researcher in advanced robotics and nonlinear control systems, with a primary focus on adaptive neural tracking control and event-triggered mechanisms for complex robotic platforms. Their most cited work, "Event-Triggered Adaptive Neural Tracking Control of Flexible-Joint Robot Systems With Input Saturation" (2022, 8 citations), addresses a critical challenge in flexible-joint robot (FJR) systems: maintaining precise tracking performance under unknown dynamics and input saturation. By replacing the saturation nonlinearity with a smooth function, Xu enables the backstepping design framework to be applied effectively, offering a robust solution that reduces communication load while ensuring stability. This contribution is particularly significant for real-world applications where robots operate under physical constraints and limited computational resources. Xu’s work bridges theoretical control design and practical implementation, making it valuable for researchers in robotics, adaptive control, and neural networks. With a growing citation record, Xu is establishing a reputation for developing intelligent, resource-efficient control strategies that push the boundaries of autonomous robotic systems.
Research Focus
Key Achievements
Top Papers
- 1