About

Mien Van is a prominent control systems researcher whose work sits at the intersection of robust control theory, fault-tolerant control, and robotics. Over the past decade, he has established himself as a leading authority on fault-tolerant control (FTC) for robot manipulators, developing innovative methodologies that ensure reliable system performance even in the presence of actuator faults, uncertainties, and disturbances. His most celebrated contributions include pioneering finite-time fault-tolerant control frameworks that combine nonsingular fast terminal sliding mode control with time delay estimation — a 2016 paper that has garnered over 470 citations — and an adaptive backstepping approach achieving comparable impact with 465 citations. These works fundamentally advanced how engineers design resilient robotic systems without requiring complete knowledge of robot dynamics. Van's research portfolio demonstrates consistent methodological innovation, progressively integrating adaptive fuzzy logic, disturbance observers, fixed-time convergence guarantees, and neural network-based fault diagnosis into increasingly sophisticated control architectures. His earlier contributions to sliding mode observers and fault diagnosis schemes laid important groundwork for the field. Collectively, his publications have accumulated over 1,200 citations, reflecting substantial influence on both academic research and practical robotics engineering worldwide.

Research Focus

Key Achievements

17
H-Index
42
Papers
1,951
Total Citations
46
Avg Citations/Paper
🏆 Most Cited Paper
Finite Time Fault Tolerant Control for Robot Manipulators Using Time Delay Estimation and Continuous Nonsingular Fast Terminal Sliding Mode Control
470 citations · 2016
📈 Most Prolific Year: 2013 (8 Papers)
🤝 Key Collaborators: 36
🏛 Institutions: National University of Singapore, University of Exeter, Queen's University Belfast, Duy Tan University, University of Ulsan, University of Warwick

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 15 days ago