Xiaoling Liang

National University of Singapore, Dalian Maritime University

Papers

Total Citations

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About

Xiaoling Liang is a leading researcher in intelligent robotic control, with a primary focus on adaptive control systems, sliding mode control, and motion reliability for robotic manipulators and rehabilitation robots. Her most influential work, "Adaptive Neural Trajectory Tracking Control for n-DOF Robotic Manipulators With State Constraints" (44 citations), introduces a groundbreaking adaptive neural control scheme that addresses parameter variations, unknown functions, and time-varying external disturbances, significantly enhancing the precision and safety of robotic operations under state constraints. Complementing this, her paper on "Adaptive nonsingular terminal sliding mode control for rehabilitation robots" (43 citations) provides a robust solution for human-robot interaction, ensuring smooth and stable motion in medical robotics. More recently, her "A deep motion reliability scheme for robotic operations" (2023, 11 citations) pioneers the integration of deep learning with reliability engineering, offering a novel framework for predicting and ensuring dependable robotic performance in complex environments. With over 100 total citations, Liang’s work bridges theoretical control theory and practical robotics, making her a key contributor to the advancement of safe, adaptive, and reliable robotic systems for industrial and healthcare applications.