Yaguang Yan
Papers
7
Total Citations
57
H-Index
5
About
Yaguang Yan is a robotics researcher whose work centers on intelligent control systems for collaborative, rehabilitation, and service robots. His primary research areas include model predictive control (MPC), trajectory tracking, and dynamic parameter identification, with a strong focus on real-world applications in emergency response, healthcare, and renewable energy. Yan’s most cited paper, “Dynamic Parameter Identification of Collaborative Robot Based on WLS-RWPSO Algorithm” (2023, 18 citations), establishes foundational methods for robot motion control and fault diagnosis. He has made significant contributions to trajectory tracking control for emergency supplies transportation robots, developing novel approaches using Koopman operator theory and event-triggered MPC to ensure timely, contactless delivery during public emergencies. His work on wearable upper limb rehabilitation robots (2024, 15 citations) applies Laguerre MPC to improve patient recovery outcomes, while his research on photovoltaic module cleaning robotic arms (2023, 7 citations) supports carbon-neutral energy goals. Yan’s innovative integration of control Lyapunov functions with predictive control further advances robotic performance in hazardous environments. With over 50 citations across his publications, Yan is establishing himself as a rising expert in practical, safety-critical robotic control systems.
Research Focus
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