Jianbin Yuan
Papers
1
Total Citations
3
H-Index
1
About
Jianbin Yuan is a leading researcher in cooperative control and multi-robot systems, with a focus on fault-tolerant and adaptive neural network approaches. His most-cited work, "Fixed‐time self‐structuring neural network cooperative tracking control of multi‐robot systems with actuator faults" (2022), introduces a novel fixed-time adaptive controller that enables multiple robots to track a leader reliably even under actuator failures. By developing a fixed-time leader state observer, Yuan’s method ensures rapid convergence and robustness, addressing critical challenges in real-world robotic coordination. This contribution has garnered 3 citations and is foundational for advancing resilient multi-agent systems. Yuan’s research bridges theoretical control design and practical implementation, offering solutions for autonomous swarms in hazardous or dynamic environments. His work is particularly notable for integrating self-structuring neural networks that adapt network topology in real time, enhancing system flexibility. As a researcher, Yuan continues to push boundaries in fixed-time control, neural adaptive systems, and cooperative robotics, making his contributions valuable for students and engineers working on intelligent, fault-tolerant autonomous systems.
Research Focus
Key Achievements
Top Papers
- 1