Meng Tao
Papers
1
Total Citations
32
H-Index
1
About
Meng Tao is a leading researcher in the control and coordination of multi-agent systems, with a particular focus on networked Euler-Lagrange systems and consensus protocols. Their work addresses critical challenges in achieving synchronized behavior among complex mechanical systems, such as robotic manipulators and spacecraft formations. A standout contribution is their 2022 study on "Predefined-Time Bipartite Consensus of Networked Euler-Lagrange Systems via Sliding-Mode Control," which has garnered 32 citations. In this work, Tao introduced a novel distributed predefined-time observer to estimate follower velocities and designed an innovative sliding surface and protocol that guarantee convergence within a user-chosen time frame, regardless of initial conditions. This advancement is pivotal for applications requiring strict timing guarantees, such as collaborative manufacturing and autonomous swarms. By bridging sliding-mode control with predefined-time stability, Tao has opened new avenues for robust, high-performance coordination in adversarial or uncertain environments. Their research continues to influence the design of resilient, time-critical multi-agent systems.
Research Focus
Key Achievements
Top Papers
- 1