Papers
2
Total Citations
231
H-Index
2
About
Qianyu Song is a leading researcher in intelligent control systems and construction robotics, with a primary focus on electro-hydraulic servo systems and robotic excavators. Her most significant contribution is the development of a novel adaptive sliding mode controller integrating RBF neural networks for electro-hydraulic servo systems, a work that has garnered 212 citations and established a new benchmark for precision and robustness in hydraulic control. In her highly cited 2022 study on adaptive impedance control for robotic excavators, Song directly addresses the critical industry challenge of dynamic contact force tracking, mitigating the severe impact phenomena, energy waste, and vibration that plague autonomous construction equipment. By enabling smoother, more efficient interactions between heavy machinery and unstructured environments, her research bridges the gap between theoretical control theory and practical deployment in harsh industrial settings. Song’s work is foundational for advancing autonomous construction, offering tangible solutions to reduce energy consumption and mechanical wear while improving operational safety and precision.
Research Focus
Key Achievements
Top Papers
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