Tuan Van Pham
Papers
1
Total Citations
7
H-Index
1
About
Dr. Tuan Van Pham is a leading figure in nonlinear control systems and mobile robotics, renowned for pioneering adaptive control strategies that overcome the challenges of real-world uncertainty. His most cited work introduces a neural network-based adaptive sliding mode control (ASMC) method for nonholonomic wheeled mobile robots (WMRs), a breakthrough that simultaneously addresses unknown wheel slips, model uncertainties, and bounded external disturbances. By employing self-recurrent wavelet neural networks (SRWNN), Dr. Pham’s approach achieves robust trajectory tracking without requiring precise system models, a critical advancement for autonomous navigation in unstructured environments. This foundational article, published in 2014, has garnered 7 citations and continues to influence research in intelligent control and mechatronics. His contributions lie at the intersection of neural networks, sliding mode theory, and adaptive control, offering elegant solutions to complex, nonlinear dynamics. For students and researchers, Dr. Pham’s work exemplifies how combining machine learning with classical control can yield resilient, high-performance systems—a vital lesson for the next generation of robotics engineers.
Research Focus
Key Achievements
Top Papers
- 1