Yu‐Long Wang
Papers
4
Total Citations
82
H-Index
3
About
Yu-Long Wang is a leading researcher in secure and cooperative control of multi-robot systems, with a focus on formation control, networked robotics, and neural network-based optimization. His work addresses critical challenges in cyber-physical systems, particularly the vulnerability of mobile robot networks to replay attacks and malicious packet losses. In his highly cited 2023 paper (37 citations), Wang developed a secure leader–follower formation control scheme for networked mobile robots under replay attacks, establishing foundational methods for resilient multi-agent coordination. His 2022 work on cross-dimensional formation control of heterogeneous multi-agent systems (24 citations) advanced the theory of coordinating agents with different dynamics. More recently, Wang introduced a harmonic noise rejection zeroing neural network for time-dependent quadratic programs (2024, 20 citations), with direct applications to robot arm control. His 2025 paper presents a cooperative learning-based tracking control approach validated through both theory and experiments, addressing modeling uncertainties and network-induced delays. With a growing citation impact and a clear trajectory from theoretical foundations to experimental validation, Wang’s research is shaping the future of secure, intelligent multi-robot systems.
Research Focus
Key Achievements
Top Papers
- 1
- 2
- 3
- 4