Yan Bin
Papers
1
Total Citations
43
H-Index
1
About
Yan Bin is a leading researcher in nonlinear control systems and intelligent robotics, with a particular focus on the stabilization and trajectory tracking of underactuated dynamical systems. His most cited work, "Extreme-learning-machine-based robust integral terminal sliding mode control of bicycle robot" (2022, 43 citations), exemplifies his innovative approach to combining machine learning with advanced sliding mode control theory. In this seminal paper, Yan Bin introduces a novel framework that leverages extreme learning machines to approximate unknown system dynamics, while designing a robust integral terminal sliding mode controller that ensures finite-time convergence and strong disturbance rejection for a self-balancing bicycle robot. This contribution addresses critical challenges in real-world robotic applications, such as model uncertainties and external perturbations, and has been widely recognized for its practical effectiveness. Yan Bin's research bridges the gap between theoretical control design and autonomous vehicle implementation, making significant strides in the field of mechatronics. His work continues to inspire new directions in adaptive and learning-based control for complex robotic systems.
Research Focus
Key Achievements
Top Papers
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