Son Tung Dang
Papers
1
Total Citations
26
H-Index
1
About
Son Tung Dang is a rising figure in the field of nonlinear control systems and mobile robotics, with a particular focus on intelligent, adaptive control strategies for complex, underactuated systems. His most cited work, an adaptive backstepping hierarchical sliding mode controller for three-wheeled mobile robots, exemplifies his core contribution: the synergistic integration of classical control theory with modern neural network techniques. By fusing a backstepping controller with a Radial Basis Function (RBF) neural network-based hierarchical sliding mode approach, Dang has pioneered a method that enhances both the robustness and adaptability of autonomous navigation in the presence of uncertainties. This work, published in 2023 and already accruing 26 citations, demonstrates a rapidly growing impact within the control engineering community. Dang’s research is notable for its practical orientation, directly addressing real-world challenges in robot stability and trajectory tracking. His achievements signal a promising trajectory in advancing intelligent, self-tuning control architectures that push the boundaries of what autonomous wheeled platforms can achieve.
Research Focus
Key Achievements
Top Papers
- 1