Papers
2
Total Citations
2
H-Index
1
About
Xuan Dang is a rising researcher in advanced robotics and nonlinear control systems, with a focus on intelligent compensation and precision trajectory tracking. Their work addresses critical challenges in controlling complex robotic structures under unstable parameters and external disturbances. In their 2024 study, Dang introduced an Adaptive Backstepping Sliding Mode Controller (ABSMC) that integrates Radial Basis Function (RBF) neural networks with a fuzzy logic modifier to effectively compensate for disturbances in dual-arm robots—a significant contribution to robust, adaptive control. Building on this, their 2025 paper presents a dynamic surface control combined with sliding mode control for precise trajectory tracking of 3-DOF delta robots, enhancing performance in high-speed automation tasks. Though early in their career, with each paper garnering 1 citation, Dang’s work demonstrates a clear trajectory toward impactful, real-world applications in manufacturing and collaborative robotics. Their innovative fusion of neural networks, fuzzy logic, and sliding mode techniques marks them as a promising contributor to the next generation of intelligent robotic control systems.
Research Focus
Key Achievements
Top Papers
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