Nguyen Gia Minh Thao
Ho Chi Minh City University of Technology, Toyota Technological Institute
Papers
4
Total Citations
117
H-Index
3
About
Nguyen Gia Minh Thao is a robotics and control systems researcher whose work spans autonomous mobile robots, rehabilitation robotics, and advanced motor drive systems. His most cited paper, a 2010 study on PID backstepping control for two-wheeled self-balancing robots (68 citations), established his expertise in nonlinear control and sensor fusion, integrating discrete Kalman filtering with robust controller design. In 2023, he contributed a comprehensive review on wearable assistive robotic devices for head and neck rehabilitation (36 citations), addressing critical physical risk factors affecting cervical spine health—a work that bridges robotics with healthcare. His industry-oriented research on autonomous mobile robots (AMRs) introduced velocity-based impedance control for manual operation modes (11 citations), directly impacting manufacturing logistics for aircraft equipment. Most recently, Thao developed a novel auto-tuning PD-fuzzy controller to reduce current harmonics in SiC-MOSFET inverter-driven motor systems (2 citations), targeting energy loss reduction in high-performance drives. His work demonstrates a rare ability to move from foundational control theory to applied industrial solutions, with cumulative citations reflecting growing influence across robotics, rehabilitation engineering, and power electronics.
Research Focus
Key Achievements
Top Papers
- 1A PID backstepping controller for two-wheeled self-balancing robot68 citations · 2010
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