Papers
10
Total Citations
172
H-Index
6
About
Luy Nguyen Tan is a control systems researcher whose work spans intelligent control, multi-agent systems, and robotic platforms, with particular expertise in H∞ optimal control, adaptive dynamic programming (ADP), and event-triggered distributed control. His research addresses some of the most challenging problems in modern control theory, including handling input constraints, external disturbances, and system uncertainties in complex interconnected systems. Among his most influential contributions is his 2019 work on event-triggered distributed H∞ constrained control for large-scale interconnected systems, which has garnered 60 citations and established him as a notable voice in distributed control design. His 2017 research on omnidirectional-vision-based optimal tracking for nonholonomic mobile multirobot systems — with 45 citations — demonstrated an impressive integration of perception and control for real-world robotic applications. Across multiple papers, he has consistently advanced reinforcement learning and ADP-based frameworks for robot manipulators and single-wheel robots, tackling asymmetric input saturation, dead-zone actuators, and cyber-attack resilience. With over 170 cumulative citations and a body of work spanning prestigious venues, Tan's contributions offer valuable tools for researchers designing robust, intelligent control systems for autonomous robots and large-scale networked agents.
Research Focus
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Top Papers
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