Zhendong Yang
Papers
1
Total Citations
15
H-Index
1
About
Zhendong Yang is a researcher whose work lies at the intersection of robotics, neural networks, and control systems, with a particular focus on solving complex kinematic challenges in redundant manipulators. His most cited paper, "Effective neural remedy for drift phenomenon of planar three-link robot arm using quadratic performance index" (2008, 15 citations), introduces a novel approach to addressing the drift phenomenon—a persistent issue in redundant robot arms where joint configurations deviate from desired trajectories over time. By employing a quadratic performance index within a neural remedy framework, Yang demonstrates how online neural computation can effectively stabilize and correct drift in real-time, validated through simulations on a three-link planar robot arm. This contribution is significant for advancing the reliability and precision of robotic systems in tasks requiring continuous, autonomous operation. While his citation count reflects a focused, specialized impact, Yang's work underscores the potential of integrating neural methods with performance optimization to solve practical engineering problems, offering valuable insights for researchers in robotics and intelligent control.
Research Focus
Key Achievements
Top Papers
- 1