Shiwei Xu
Papers
1
Total Citations
8
H-Index
1
About
Shiwei Xu is a leading researcher in advanced robotic 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 critical challenges in flexible-joint robot (FJR) systems by developing a novel control framework that mitigates unknown dynamics and input saturation. By replacing the input saturation nonlinearity with a smooth function, Xu enables the effective implementation of backstepping design, significantly enhancing system stability and performance. This contribution is pivotal for real-world applications where precision and energy efficiency are paramount, such as in industrial automation and assistive robotics. Xu’s research not only advances theoretical understanding but also provides practical solutions for robust, adaptive control in uncertain environments. Their work continues to inspire innovations in event-triggered control, making them a notable figure in the field of robotics and automation.
Research Focus
Key Achievements
Top Papers
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