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

16
H-Index
27
Papers
1,309
Total Citations
48
Avg Citations/Paper
🏆 Most Cited Paper
A combined backstepping and small-gain approach to robust adaptive fuzzy control for strict-feedback nonlinear systems
398 citations · 2004
📈 Most Prolific Year: 1995 (3 Papers)
🤝 Key Collaborators: 42
🏛 Institutions: City University of Hong Kong, UNSW Sydney, RMIT University, Grenoble Images Parole Signal Automatique, University of Melbourne

Top Papers

  1. 1
  2. 2
  3. 3
  4. 4
  5. 5
  6. 6
  7. 7
  8. 8
  9. 9
  10. 10

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago