Tengda Dai

Papers

Total Citations

H-Index

About

Tengda Dai is a robotics and control systems researcher whose work centers on the dynamics and intelligent control of parallel robotic systems, with a particular focus on the challenging intersection of rigid-flexible coupling mechanics and advanced control algorithms. Their most influential contribution, "Adaptive Sliding Mode Neural Network Control and Flexible Vibration Suppression of a Flexible Spatial Parallel Robot" (2021), has garnered 23 citations and introduced a novel adaptive sliding mode control algorithm enhanced by neural networks to address elastic deformation-induced vibrations in flexible spatial parallel robots — a persistent challenge in high-precision robotic applications. Complementing this, their 2020 work on dynamics analysis of spatial parallel robots with rigid and flexible links, accumulating 6 citations, provided a rigorous dynamic modeling framework using floating frame of reference formulation, advancing understanding of rigid-flexible coupling effects on robotic performance. Together, these contributions demonstrate Dai's commitment to bridging theoretical modeling with practical control solutions, improving both computational efficiency and operational stability in next-generation parallel robotic systems. Their research holds significant implications for precision manufacturing, aerospace, and other fields demanding high-performance robotic manipulation.