Papers
8
Total Citations
57
H-Index
4
About
Van-Anh Nguyen is a robotics and control systems researcher whose work sits at the intersection of advanced control theory and practical robotic applications. Specializing in nonlinear control design, fuzzy logic systems, and sliding mode control, Nguyen has made meaningful contributions to some of the most challenging problems in modern robotics, including trajectory tracking for serial manipulators, underactuated mobile robots, and cable-driven parallel systems. Nguyen's most influential work, "Nonlinear Tracking Control with Reduced Complexity of Serial Robots: A Robust Fuzzy Descriptor Approach" (2019, 20 citations), introduced a descriptor Takagi-Sugeno fuzzy framework that elegantly reduced control complexity without sacrificing robustness — a significant practical advancement for real-world robot manipulator deployment. This line of research was further refined through guaranteed L∞ error-bound formulations, addressing a gap that had long persisted in the manipulator control literature. Beyond serial robots, Nguyen has extended expertise to two-wheeled balancing robots, integrating hierarchical sliding mode control with nature-inspired optimization via the Firefly Algorithm, and to cable-driven parallel robots using Interval Type-2 fuzzy controllers. More recently, work on ball-balancing robots incorporating Control Barrier Functions with Model Predictive Control signals a growing focus on safe autonomous navigation. With over 55 cumulative citations, Nguyen represents an emerging voice in intelligent, robust robotic control.
Research Focus
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Top Papers
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- 8Experimental validation of dynamic models for high-speed Delta robots2 citations · 2025