Papers
27
Total Citations
1,309
H-Index
16
About
Gang Feng is a distinguished researcher whose work spans intelligent control systems, robotics, and multi-agent coordination — fields in which he has made lasting and widely recognized contributions. His pioneering 2004 paper on robust adaptive fuzzy control for strict-feedback nonlinear systems, which has accumulated nearly 400 citations, established a landmark framework for handling unstructured uncertainties through a combined backstepping and small-gain approach, significantly advancing the theoretical foundations of adaptive control. His earlier work on sliding-mode-based adaptive fuzzy control for robot manipulators (1999) and neural network compensation schemes (1995) reflect a sustained commitment to intelligent, learning-based robotic control. Feng's research extends naturally into multi-robot systems, where his synchronization-based approach to trajectory tracking while maintaining time-varying formations (225 citations) offered an elegant and practical solution to coordinated mobile robotics. He has further explored formation control under communication failures, bearing-only measurements, and target entrapment strategies, demonstrating both theoretical depth and real-world applicability. More recently, his work on quantized fuzzy cooperative output regulation for heterogeneous multi-agent systems and automated biological cell manipulation highlights his evolving interdisciplinary reach. Across more than two decades, Feng's body of work reflects a rare combination of rigorous mathematical innovation and tangible engineering impact.
Research Focus
Key Achievements
Top Papers
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- 4An adaptive fuzzy controller based on sliding mode for robot manipulators91 citations · 1999
- 5A compensating scheme for robot tracking based on neural networks54 citations · 1995
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