Yongling Li
Papers
1
Total Citations
3
H-Index
1
About
Yongling Li is a researcher specializing in intelligent control systems, with a particular focus on robotic manipulators and neural-network-based decoupling strategies. Their most notable contribution is the development of a composite control algorithm that integrates artificial neural networks (ANN) with a th-order inverse system method and PID control, designed to enhance trajectory tracking in robotic manipulators with unknown dynamics. This work, published in 2005, introduces a novel approach to approximately decouple complex, nonlinear robotic systems, improving precision and adaptability in real-time control. Though the paper has garnered 3 citations, it represents a foundational step in bridging neural network theory with practical robotic applications. Li’s research addresses critical challenges in automation and robotics, offering a pathway toward more robust, self-tuning manipulators. Their work is particularly relevant for students and researchers exploring intelligent control, nonlinear system decoupling, and the integration of machine learning into industrial robotics.
Research Focus
Key Achievements
Top Papers
- 1