Xinru Lin
Papers
1
Total Citations
1
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About
Xinru Lin is a researcher in the field of robotics and intelligent control systems, with a primary focus on trajectory tracking and adaptive control for space robotic manipulators. Her most notable contribution is the development of a hybrid control strategy that integrates wavelet neural networks (WNN) with sliding mode control (SMC), first presented in her 2022 paper on two-joint space robots. This work addresses the challenging problem of precise trajectory tracking under periodic interference, a critical issue for autonomous space operations. By combining the nonlinear approximation capabilities of WNN with the robustness of SMC, Lin proposed a novel framework that enhances system stability and disturbance rejection. While her work is still early in its citation impact, it represents a meaningful step toward more reliable control of multi-link robotic systems in space environments. Her research interests lie at the intersection of neural network-based learning and classical control theory, aiming to improve the performance of robots operating in unstructured or remote settings. Lin’s contributions are particularly relevant for students and researchers exploring intelligent control methods for aerospace and industrial robotics.
Research Focus
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Top Papers
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