Hai Tuan Pham
Papers
2
Total Citations
38
H-Index
2
About
Hai Tuan Pham is a leading researcher in advanced robotics control, specializing in adaptive neural network-based strategies for complex robotic systems. His work focuses on developing robust control methods for dual-arm robots, addressing the inherent uncertainties and nonlinearities in their dynamics. Pham’s major contributions include pioneering a backstepping sliding mode control approach integrated with neural networks, which significantly enhances trajectory tracking and stability in cooperative manipulation tasks. His most cited paper, “Adaptive Neural Network-Based Backstepping Sliding Mode Control Approach for Dual-Arm Robots” (2019), has garnered 35 citations, reflecting its influence in the field. Additionally, his research on dynamic surface control for uncertain dual-arm robots (2019) further advances adaptive control theory, offering solutions for real-time applications. Pham’s work is notable for bridging theoretical control design with practical implementation, providing a foundation for safer and more efficient human-robot collaboration. His contributions are instrumental for students and researchers exploring intelligent control systems, particularly in the context of multi-robot coordination and adaptive learning.
Research Focus
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Top Papers
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