Zhu Yinfa
Papers
2
Total Citations
58
H-Index
2
About
Zhu Yinfa is a leading researcher in the control and dynamics of free-floating space robotic manipulators, a critical area for autonomous on-orbit servicing and debris removal. His work focuses on overcoming the unique challenges of controlling robotic arms mounted on spacecraft without fixed bases, where uncertainties and nonlinear dynamics are prevalent. Zhu’s most influential contribution is his 2013 paper on output feedback control using an adaptive fuzzy neural network, which has garnered 50 citations for its innovative approach to trajectory tracking without full-state measurement. In his earlier foundational work (2012), he pioneered a neural network adaptive control strategy that directly identifies the uncertain nonlinear system model in task space, enabling precise trajectory tracking even when the system model is unknown. These contributions have established a robust framework for intelligent control in space robotics, directly impacting the development of more autonomous and reliable space manipulators. Zhu’s research is essential reading for engineers and researchers working at the intersection of neural networks, adaptive control, and space robotics.
Research Focus
Key Achievements
Top Papers
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