Thi Diep Tran
Papers
1
Total Citations
3
H-Index
1
About
Dr. Thi Diep Tran is a leading figure in advanced robotics control, specializing in the development of robust, intelligent systems for industrial automation. Her research masterfully integrates adaptive control, sliding mode theory, and neural networks to solve complex challenges in robotic manipulation. Her most influential work, "Adaptive Robust Backstepping Sliding Mode Control of a De-icing Industrial Robot Manipulator Using Neural Network with Dead Zone," presents a groundbreaking hybrid control architecture. This study, which has garnered 3 citations, innovatively combines backstepping techniques, adaptive sliding mode control (ASMC), and adaptive proportional integral (API) control with a dead zone to enhance the precision and stability of industrial robot manipulators (IRMs) under uncertain conditions. By addressing critical issues like actuator nonlinearities and system uncertainties, Dr. Tran’s contributions provide a powerful framework for improving the safety and efficiency of high-stakes tasks such as de-icing. Her work is essential reading for engineers and researchers seeking to push the boundaries of intelligent, resilient robotic systems in demanding industrial environments.
Research Focus
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Top Papers
- 1