Thien Nguyen Van
Papers
1
Total Citations
3
H-Index
1
About
Thien Nguyen Van is a researcher in robotics and intelligent control systems, with a focus on enhancing the autonomy and stability of robotic manipulators. His most-cited work, "Reinforcement Control for Planar Robot Based on Neural Network and Extended State Observer" (2023), introduces a novel hybrid control framework that integrates reinforcement learning with neural networks and extended state observers. This approach addresses critical challenges in real-time robot control, such as disturbance rejection and adaptive learning in uncertain environments, offering a pathway toward more resilient and self-optimizing robotic systems. Though early in its citation impact (3 citations), the paper has been recognized for its innovative fusion of model-free and model-based techniques, laying groundwork for future advances in adaptive robotics. Van’s research contributes to the broader fields of nonlinear control, neural network-based estimation, and reinforcement learning applications in mechatronics. His work is particularly relevant for students and researchers exploring robust control strategies for planar robots and other underactuated systems, where precision and adaptability are paramount.
Research Focus
Key Achievements
Top Papers
- 1