Papers
4
Total Citations
56
H-Index
3
About
Tuan Anh Phan is a robotics researcher whose work bridges the gap between adaptive control theory and biologically inspired swarm intelligence. His primary research areas include adaptive neural network control, sliding mode control, and swarm robotics coordination. Dr. Phan’s most significant contribution lies in developing adaptive neural network-based backstepping sliding mode control for dual-arm robots, a method that enables precise manipulation under uncertainty—his 2019 paper on this topic has garnered 35 citations, reflecting its impact on advanced robotic manipulation. Earlier in his career, he pioneered swarm robot methodologies for collaborative manipulation of non-identical objects, drawing inspiration from biological leaf-curling behaviors. His 2011 and 2010 papers, with 10 and 8 citations respectively, introduced algorithms that significantly improved task completion rates in swarm systems using sematectonic stigmergy—a form of indirect communication. These works demonstrate his ability to translate natural collective behaviors into effective robotic coordination. Dr. Phan’s research not only advances theoretical foundations in adaptive control but also provides practical solutions for multi-robot systems, making him a notable contributor to both industrial automation and swarm robotics fields.
Research Focus
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