Papers
168
Total Citations
7,044
H-Index
48
About
Yunong Zhang is a prolific researcher whose work sits at the dynamic intersection of neural computing, robotics, and optimization. Best known for pioneering the Zhang Neural Network (ZNN) framework, Zhang has fundamentally advanced how recurrent neural networks are applied to real-time computational problems, particularly time-varying matrix inversion and quadratic programming. His noise-robust ZNN variants — including the Integration-Enhanced ZNN and Modified ZNN — address the critical practical challenge of solving time-sensitive problems in noisy environments, garnering over 500 combined citations. In robotics, Zhang has made landmark contributions to the kinematic control and redundancy resolution of robot manipulators, developing neural and optimization-based schemes for obstacle avoidance, joint-drift correction, and tracking control with unknown models. His dual neural network for redundancy resolution (2003, 250 citations) remains a foundational reference in the field. Zhang has further extended his methods to humanoid and dual-arm robotic systems, demonstrating versatility and real-world applicability. With his ten most-cited papers collectively amassing over 2,100 citations, Zhang's body of work represents a cornerstone of modern neurocomputational robotics, making him an essential reference for researchers tackling intelligent motion planning and control challenges.
Research Focus
Key Achievements
Top Papers
- 1Kinematic Control of Redundant Manipulators Using Neural Networks329 citations · 2016
- 2
- 3
- 4
- 5
- 6
- 7Repetitive Motion Planning and Control of Redundant Robot Manipulators166 citations · 2013
- 8G2-Type SRMPC Scheme for Synchronous Manipulation of Two Redundant Robot Arms155 citations · 2014
- 9
- 10