Thi-Van-Anh Nguyen

Hanoi University of Science and Technology

Papers

Total Citations

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About

Thi-Van-Anh Nguyen is a rising researcher in advanced robotics and intelligent control systems, with a focus on nonlinear dynamics, fuzzy logic, and bio-inspired optimization. Her work centers on developing robust control strategies for complex robotic platforms, including two-wheeled self-balancing mobile robots and cable-driven parallel manipulators. In her highly cited 2026 paper, she introduced a novel trajectory tracking framework for self-balancing robots that integrates Model Predictive Path Following (MPPF) with constrained Higher-Order Sliding Mode Control (HSMC) and Interval Type-2 Fuzzy Logic, achieving superior stability and precision under uncertainty. Her second major contribution applies a modified Shark Smell Algorithm to optimize Interval Type-2 Fuzzy controllers for an 8-cable-driven parallel robot, demonstrating enhanced tracking accuracy in high-dimensional systems. Though early in her career, Nguyen’s work has already garnered attention for its innovative fusion of fuzzy logic with metaheuristic optimization, addressing real-world challenges in robot autonomy and manufacturing. Her research promises significant impact in human-robot interaction, rehabilitation robotics, and industrial automation, marking her as a promising voice in the next generation of control engineering.