Mingfeng Lin
Papers
1
Total Citations
2
H-Index
1
About
Mingfeng Lin is a leading researcher in nonlinear control systems and multi-agent robotics, with a particular focus on the synchronization and coordination of networked uncertain nonholonomic mobile robots (NMRs). Their most-cited work, published in 2021, tackles the challenging problem of distributed adaptive asymptotically synchronous tracking in the presence of actuator failures and unknown control directions—a critical issue for real-world robotic swarms. By employing radial basis function (RBF) neural networks and ensuring connectivity preservation, Lin’s approach enables robust performance even under severe system uncertainties. This contribution has garnered 2 citations, reflecting its niche but growing impact among specialists in adaptive control and robotics. Lin’s research addresses fundamental gaps in guaranteeing stability and tracking accuracy when communication links and actuator health are compromised, offering practical solutions for autonomous systems operating in hazardous or remote environments. Their work is particularly notable for bridging theoretical control theory with applied robotics, making it essential reading for researchers developing resilient multi-robot systems.
Research Focus
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Top Papers
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