Thanh Nguyen Truong
Papers
19
Total Citations
433
H-Index
11
About
Thanh Nguyen Truong is a prominent researcher specializing in advanced control systems for robotic manipulators, with particular expertise in sliding mode control, neural network-based controllers, and robust trajectory tracking. His work addresses some of the most pressing challenges in robotics: handling uncertain dynamics, achieving finite- and fixed-time convergence, and maintaining high-precision performance under real-world disturbances. Truong's most influential contribution, a backstepping global fast terminal sliding mode controller for industrial robotic manipulators (2021, 154 citations), introduced an integral sliding mode surface that significantly improves dynamic performance and convergence speed—a foundational advance widely adopted by subsequent researchers. His broader portfolio demonstrates a systematic effort to push controller capabilities further, incorporating prescribed performance guarantees, fault-tolerant mechanisms, observer-based strategies, and neural network adaptations to overcome model uncertainty and input saturation constraints. His 2023 review of neural network-based sliding mode controllers (53 citations) has established itself as an essential reference for researchers entering this field. Across ten highly cited publications accumulating over 370 citations, Truong has consistently bridged theoretical rigor with practical applicability, making meaningful contributions to intelligent, resilient robotic control systems that perform reliably in complex industrial environments.
Research Focus
Key Achievements
Top Papers
- 1
- 2
- 3
- 4
- 5
- 6
- 7
- 8
- 9
- 10