Xinglong Zhang
Papers
1
Total Citations
8
H-Index
1
About
Xinglong Zhang is a robotics and control systems researcher whose work centers on intelligent control methodologies for robotic manipulators, with a particular focus on addressing real-world challenges in dynamic and uncertain environments. His most recognized contribution introduces an Adaptive Fuzzy Sliding Mode Controller with Nonlinear Observer (AFSMCO), a sophisticated framework designed to enable redundant robotic manipulators to achieve precise trajectory tracking in task space while handling varying payloads — a critical challenge in industrial and collaborative robotics applications. By combining fuzzy logic, sliding mode control, and nonlinear observation techniques, Zhang's approach elegantly addresses system uncertainties and disturbances that commonly plague traditional control strategies. This work, which has garnered 8 citations since its 2016 publication, demonstrates his ability to bridge theoretical control design with practical robotic implementation. His research is particularly relevant for engineers and researchers working on flexible manufacturing systems, human-robot collaboration, and autonomous manipulation, where payload variability and environmental uncertainty demand robust, adaptive solutions. Zhang's contributions reflect a commitment to advancing intelligent control paradigms that make robotic systems more reliable, adaptable, and capable in complex operational settings.
Research Focus
Key Achievements
Top Papers
- 1