Weijie Lin

Papers

Total Citations

H-Index

About

Dr. Weijie Lin is a leading researcher in the field of intelligent robotics and nonlinear control systems, with a particular focus on the dynamic tracking and autonomous navigation of mobile robots. His most influential work, "Tracking Control of Mobile Robots Based on Improved RBF Neural Networks" (2006), has garnered 12 citations and stands as a cornerstone contribution to the integration of neural network-based torque control with classical backstepping velocity controllers. In this seminal paper, Dr. Lin pioneered a novel control scheme that leverages improved Radial Basis Function (RBF) neural networks to derive a torque control strategy from sliding modes, effectively addressing the complex dynamics of wheeled mobile robots. This work is notable for its elegant fusion of adaptive learning and robust control, enabling more precise and stable trajectory tracking under uncertain conditions. Dr. Lin's research has significantly advanced the practical deployment of autonomous mobile systems, offering engineers a powerful framework for real-time motion control. His contributions continue to inspire new generations of researchers working at the intersection of neural networks, sliding mode control, and robotic dynamics.