Angbo Xie
Papers
1
Total Citations
1
H-Index
1
About
Angbo Xie is a researcher focused on advanced control systems for robotic manipulators, particularly in the domain of space robotics. Their work centers on developing robust trajectory-tracking algorithms that can withstand periodic disturbances and system uncertainties. In their most notable contribution, Xie proposed an innovative hybrid control strategy combining wavelet neural networks (WNN) with sliding mode control (SMC) for two-joint space robots. This approach leverages the adaptive learning capabilities of WNN to approximate nonlinear dynamics while employing SMC's inherent robustness against external perturbations, effectively addressing the complex challenge of precise motion control in space environments. Though early in its citation impact, this work represents a meaningful step toward more reliable autonomous operations for orbital robotic systems. Xie's research sits at the intersection of neural network-based intelligent control and classical nonlinear control theory, offering practical solutions for real-world applications where traditional methods fall short. Their work continues to explore how adaptive learning algorithms can enhance the performance of robotic systems operating under uncertain or changing conditions.
Research Focus
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Top Papers
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