Papers

12

Total Citations

283

H-Index

9

About

Mai The Vu is a prominent robotics and control systems researcher whose work spans advanced control theory, intelligent systems, and robotic applications. His research primarily focuses on sliding mode control, fuzzy logic systems, neural networks, and disturbance observer-based methods applied to complex robotic platforms including underactuated systems, exoskeletons, cable-driven parallel robots, and wheeled mobile robots. Among his most influential contributions is a fast terminal sliding mode control framework leveraging finite-time disturbance observers for underactuated robotic systems, which has garnered 65 citations since 2021, underscoring its significance to the control community. His work on optimized fuzzy-enhanced robust control for Stewart parallel robots (41 citations) and fuzzy-based fixed-time nonsingular tracking for rehabilitation exoskeletons (30 citations) demonstrates his dedication to bridging theoretical rigor with real-world assistive and industrial applications. Notably, his early research on underwater construction robots reflects a versatile engineering background that has evolved into sophisticated intelligent control design. With over 270 cumulative citations across a focused body of work, Mai The Vu has established himself as an impactful voice in modern robotics control, consistently advancing methods that improve precision, robustness, and adaptability in challenging dynamic environments. His research holds particular relevance for students exploring intelligent control, rehabilitation robotics, and autonomous systems.

Research Focus

Key Achievements

9
H-Index
12
Papers
283
Total Citations
24
Avg Citations/Paper
🏆 Most Cited Paper
Fast Terminal Sliding Control of Underactuated Robotic Systems Based on Disturbance Observer with Experimental Validation
65 citations · 2021
📈 Most Prolific Year: 2022 (5 Papers)
🤝 Key Collaborators: 37
🏛 Institutions: Sejong University, Korea Maritime and Ocean University, Korea Institute of Ocean Science and Technology

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 15 days ago