Papers
16
Total Citations
116
H-Index
5
About
Hai Xuan Le is a prominent robotics and control systems researcher whose work centers on intelligent control strategies for complex robotic platforms, including dual-arm robots, mobile robots, and underactuated systems. His research consistently addresses the critical challenge of maintaining robust performance in the face of system uncertainties, nonlinearities, and external disturbances — problems that are central to real-world robotics deployment. Le's most recognized contribution, his 2019 work on adaptive neural network-based backstepping sliding mode control for dual-arm robots (35 citations), established a foundation for combining neural network adaptability with sliding mode robustness. This theme continues throughout his portfolio, spanning hierarchical sliding mode control for three-wheeled mobile robots (26 citations), dynamic surface control methods (15 citations), and fuzzy hierarchical approaches for underactuated SIMO systems (8 citations). His more recent investigations extend into reinforcement learning and adaptive dynamic programming, reflecting an evolving integration of data-driven techniques into classical control frameworks. Across his body of work, Le has accumulated over 100 citations, demonstrating meaningful influence within the intelligent robotics control community. His research offers students and engineers practical, theoretically grounded frameworks for tackling some of the most persistent challenges in autonomous robotic systems.
Research Focus
Key Achievements
Top Papers
- 1
- 2
- 3
- 4
- 5
- 6
- 7
- 8
- 9
- 10