Papers

4

Total Citations

50

H-Index

3

About

Fuxi Wan is a rising researcher in the field of advanced robotics control, with a primary focus on the adaptive neural control of uncertain robotic manipulators. Wan’s major contributions lie in developing novel sliding mode control strategies that achieve predefined-time and fixed-time convergence, even under challenging conditions such as input saturation, dead zone nonlinearities, and prescribed constraints. By integrating radial basis function neural networks into these control frameworks, Wan has created robust, adaptive solutions that significantly enhance the stability and precision of robotic systems in real-world applications. Wan’s most cited works, including “Adaptive neural sliding mode control of uncertain robotic manipulators with predefined time convergence” (19 citations) and its fixed-time counterpart (16 citations), have established a strong foundation for time-critical robotic operations. More recently, Wan has expanded into bio-inspired robotics, exploring a maneuverable winding gait for snake robots using a delay-aware swing and grasp framework that combines rule-based and learning methods. With over 50 cumulative citations, Wan’s work is gaining traction among control engineers and roboticists, offering practical pathways for safer, faster, and more reliable autonomous manipulation.

Research Focus

Key Achievements

3
H-Index
4
Papers
50
Total Citations
13
Avg Citations/Paper
🏆 Most Cited Paper
Adaptive neural sliding mode control of uncertain robotic manipulators with predefined time convergence
19 citations · 2022
📈 Most Prolific Year: 2022 (3 Papers)
🤝 Key Collaborators: 7
🏛 Institutions: South China University of Technology, Nankai University

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 15 days ago