Papers
7
Total Citations
192
H-Index
5
About
Xiru Wu is a leading researcher in advanced robotics and intelligent control systems, with a primary focus on multi-robot coordination, adaptive control, and vision-based automation. Their most influential work, an adaptive fractional-order non-singular terminal sliding mode control using fuzzy wavelet neural networks for omnidirectional mobile robot manipulators (82 citations), has significantly advanced robust control theory for complex robotic systems. Wu's earlier foundational contribution on neural network robust H∞ tracking control for robot manipulators (55 citations) established key stability guarantees in uncertain environments. Their research on observer-based leader-following formation control with obstacle avoidance (32 citations) has been instrumental in enabling safe multi-robot coordination, while their deep learning approach to location recognition for industrial sorting robots (13 citations) bridges computer vision and manufacturing automation. More recently, Wu has explored quantized event-triggered control for Markov jump systems and distributed formation control using complex Laplacians, demonstrating continued innovation in networked robotics. With over 190 total citations across their portfolio, Wu's work has directly impacted both theoretical control methodologies and practical applications in industrial and epidemic prevention robotics.
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