Tianhang Chen
Papers
2
Total Citations
16
H-Index
2
About
Tianhang Chen is a robotics researcher whose work focuses on improving the precision and adaptability of robotic joint systems, particularly those employing flexible joints and harmonic drives. His major contributions lie in developing advanced control and estimation techniques to address real-world challenges in robot manipulation. In his highly cited 2023 paper, "An Adaptive Torque Observer Based on Fuzzy Inference for Flexible Joint Application," Chen introduced a novel fuzzy inference-based observer that dynamically adapts to changing robot configurations, significantly enhancing torque estimation accuracy for permanent magnet synchronous machine (PMSM)-driven joints—a critical advancement for applications requiring consistent performance during continuous motion. This work has garnered 11 citations, underscoring its relevance. Earlier, Chen's 2018 study, "Kinematic Model of Harmonic Drive in Robot Joints with Input Eccentricity Error," provided a foundational kinematic model that accounts for manufacturing imperfections, offering a more realistic framework for joint control. With 5 citations, this work highlights his attention to practical error sources. Chen's research bridges theoretical modeling and adaptive control, making him a notable contributor to the field of robotic actuation and precision motion control.
Research Focus
Key Achievements
Top Papers
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