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About

Nga Thi-Thuy Vu is a robotics and control systems researcher whose work centers on the development of advanced control algorithms for wheeled mobile robots (WMRs). Her research addresses some of the most persistent challenges in mobile robotics, including system uncertainties, external disturbances, and wheel slippage — factors that significantly degrade real-world robot performance. Vu has made notable contributions through the design of observer-based adaptive controllers, adaptive fuzzy type-II controllers, and sliding mode control (SMC) frameworks, each offering robust solutions for precise position and velocity tracking under unpredictable operating conditions. Her dual-loop control architecture — combining outer-loop position tracking with inner-loop velocity regulation — reflects a sophisticated systems-level approach to robot control design. More recently, Vu has expanded into data-driven and intelligent control methodologies, exploring Q-learning-based adaptive optimal control strategies that reduce reliance on explicit system models. Her publications, accumulating approximately 30 citations since 2020, demonstrate a steadily growing research profile. Through her progression from classical adaptive control to reinforcement learning-inspired techniques, Vu represents an emerging voice in intelligent robotics, contributing practical and theoretically grounded solutions to autonomous mobile robot navigation.