Papers
31
Total Citations
887
H-Index
17
About
Anh Tuan Vo is a prominent control systems researcher whose work centers on advanced robust control strategies for industrial robotic manipulators, with particular expertise in sliding mode control, fault-tolerant systems, and intelligent control methodologies. His research has made substantial contributions to solving longstanding challenges in robotic trajectory tracking, including singularity elimination, finite-time convergence, and resilience under dynamic uncertainties and actuator faults. Vo's most influential work, a backstepping global fast terminal sliding mode controller published in 2021, has accumulated 154 citations and introduced an innovative integral sliding surface formulation that significantly enhances dynamic performance and convergence speed. Across multiple highly cited studies, he has systematically advanced non-singular fast terminal sliding mode control frameworks, integrating adaptive mechanisms, neural network approximators, and third-order sliding mode observers to handle unknown disturbances and velocity estimation without tachometer sensors. His 2023 review of neural network-based sliding mode controllers has rapidly become a key reference in the field, reflecting his broader scholarly influence. Collectively, Vo's publication record exceeds 650 citations, demonstrating considerable community impact. His recent work on model-free, fixed-time prescribed performance control signals a continued commitment to pushing the boundaries of practically deployable, mathematically rigorous robotic control, making his research portfolio essential reading for engineers and students working in intelligent motion control and autonomous robotic systems.
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