Dinh-Hieu Phan
Papers
4
Total Citations
28
H-Index
4
About
Dinh-Hieu Phan is a rising researcher in robotics and control systems, whose work focuses on the stability, autonomy, and security of intelligent robotic platforms. His primary contributions lie in the development of advanced control strategies for two-wheeled self-balancing robots (TWSBRs), where he has proposed adaptive nonlinear PD controllers and genetically optimized PID controllers to enhance robustness against external forces and dynamic uncertainties. Phan’s research also extends to human tracking and multi-robot systems, where he has improved the Camshift algorithm by integrating deep learning (YOLOv4-tiny) and Kalman filtering for real-time surveillance applications, and has addressed critical challenges in networked robotic manipulators by designing resilient consensus control protocols resilient to actuator faults and deception attacks. His most cited work, an adaptive nonlinear PD controller for TWSBRs, has garnered 13 citations, reflecting its practical relevance in balancing and disturbance rejection. With publications spanning 2023 to 2025, Phan is establishing himself as a versatile engineer, bridging classical control theory with modern AI and cybersecurity concerns—a promising trajectory for advancing safe and autonomous robotics.
Research Focus
Key Achievements
Top Papers
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