Papers
3
Total Citations
65
H-Index
3
About
Le Yin has made pioneering contributions at the intersection of intelligent control, fault-tolerant robotics, and industrial automation. His foundational work on robust adaptive dead-zone technology for fault-tolerant control of robot manipulators, published in 2002 with 42 citations, introduced a neural network-based framework that ensures system stability even under actuator failures—a critical advancement for safety-critical robotic applications. Expanding on this, his 2001 paper developed a discrete-time radial basis function (RBF) neural network for fault accommodation in robotic systems, featuring a robust learning algorithm with an adaptive dead-zone technique that guarantees convergence of network parameters. This work has been instrumental in enabling robots to maintain performance despite sensor or actuator degradation. More recently, Yin has advanced industrial automation through his 2024 study on calibration and pose measurement for a combined vision sensor system, enabling precise robot grasping of brackets with 9 citations. His research seamlessly bridges theoretical control theory with practical instrumentation, demonstrating lasting impact in both academic citations and real-world manufacturing applications.
Research Focus
Key Achievements
Top Papers
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