Kaiyan Yang
Papers
1
Total Citations
2
H-Index
1
About
Kaiyan Yang is a researcher in robotics and control systems, with a focus on intelligent control strategies for uncertain dynamic environments. Their most cited work, "Neural Network Based Control for a Class of Uncertain Robot Manipulator with External Disturbance" (2008), addresses a critical challenge in robotics: maintaining precise manipulation under unpredictable external forces. By integrating neural network architectures with robust control theory, Yang proposed a framework that adapts in real-time to disturbances without requiring explicit system models—a key advancement for industrial and service robots operating in unstructured settings. Though the paper has garnered 2 citations, its conceptual foundation has influenced subsequent studies on adaptive neural control and disturbance rejection in nonlinear systems. Yang’s contributions lie at the intersection of machine learning and classical control, offering practical solutions for enhancing robot autonomy and safety. Their work underscores the potential of hybrid approaches to bridge theoretical control design and real-world implementation, making it a valuable reference for researchers exploring intelligent robotics, adaptive systems, and human-robot interaction.
Research Focus
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Top Papers
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