Xiangyong Chen
Papers
5
Total Citations
67
H-Index
4
About
Xiangyong Chen is a researcher whose work bridges the frontiers of multi-agent systems, nonlinear control theory, and human–computer interaction. His primary contributions lie in developing advanced control strategies for complex, uncertain environments. Notably, he has pioneered distributed adaptive finite-time tracking for multi-agent systems, a method that ensures rapid and robust coordination among autonomous agents, with applications ranging from robotics to sensor networks. His work on finite-time energy-to-peak fuzzy filtering for switched nonlinear systems with unreliable links addresses critical challenges in networked control, ensuring stability and performance despite communication faults. Chen has also made significant strides in human emotion recognition, proposing an attention-based sensor fusion framework that combines convolutional neural networks with weighted kernel support vector machines to decode emotions from human motion captured by inertial measurement units. This work, with 22 citations, highlights his ability to apply control theory to real-world human–computer interaction challenges. His research on observer-based prescribed-time consensus for nonlinear multiagent systems under stochastic switching topologies (2025) further demonstrates his leadership in time-critical coordination. With over 67 total citations across his most-cited works, Chen’s contributions are shaping the future of autonomous systems and intelligent human–machine interfaces.
Research Focus
Key Achievements
Top Papers
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