Teng‐Fei Ding
Papers
9
Total Citations
270
H-Index
7
About
Teng-Fei Ding is a leading researcher in the control and coordination of networked robotic systems, with a focus on bipartite tracking, formation control, and hierarchical hybrid control strategies. His work addresses critical challenges in multi-robot systems operating under signed directed graphs, quantized-data interactions, and time-varying delays. Ding’s major contributions include the development of hierarchical hybrid control algorithms (HHCAs) that integrate continuous and discontinuous signals for bipartite tracking, achieving robust performance under input disturbances and discrete communications. His research on lag-bipartite formation tracking over directed matrix-weighted signed graphs has advanced the understanding of cooperative and antagonistic interactions in robotic networks. With over 270 citations from his most-cited papers, including 66 citations for his 2020 work on discrete-communication-based bipartite tracking, Ding’s impact is evident. Notable achievements include his work on cluster time-varying formation-containment tracking using prescribed-time extended state observers (ESOs) and adaptive finite-time control for teleoperation mobile robots. His recent exploration of reinforcement learning for adaptive path planning and formation control demonstrates his forward-thinking approach. Ding’s research is essential for students and researchers interested in distributed control, multi-agent systems, and the practical deployment of networked robots in complex environments.
Research Focus
Key Achievements
Top Papers
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