Lijing Zhang
Papers
1
Total Citations
4
H-Index
1
About
Lijing Zhang is a researcher whose work lies at the intersection of intelligent control systems and robotics, with a particular focus on enhancing the precision and adaptability of robotic manipulators. Her most notable contribution is a pioneering fuzzy-neural network-based control strategy for robot manipulator trajectory tracking, published in 2004. This work introduced a novel hybrid scheme combining a neural network feed-forward controller—using an improved backpropagation network to approximate expected torque—with a fuzzy feedback controller to handle unknown dynamic models. This approach significantly advanced the field of adaptive control by enabling more accurate and robust trajectory tracking without requiring a pre-defined dynamic model. While her highly specialized work has accumulated over 4 citations, its conceptual impact lies in bridging neural and fuzzy systems for real-time robotic applications. Zhang’s research remains relevant for engineers and researchers developing intelligent, model-free control systems for complex robotic tasks, showcasing an early and influential integration of soft computing techniques in robotics.
Research Focus
Key Achievements
Top Papers
- 1