Papers
4
Total Citations
302
H-Index
4
About
Huiyan Lu is a leading researcher in neural dynamics and robotics, whose work focuses on solving complex, time-varying problems in real-time control systems. Her core contributions lie in the development of advanced recurrent neural networks (RNNs) and zeroing neural networks (ZNNs) for motion generation and linear system solving under perturbation. Notably, her 2019 paper on an RNN for perturbed time-varying underdetermined linear systems has garnered 163 citations, establishing a foundational method for handling double bound limits on residual errors and state variables. She has also pioneered a joint-drift-free scheme for redundant robot manipulators (66 citations), addressing critical failures in task execution, and introduced saturation-allowed neural dynamics (66 citations) for perturbed systems of linear equations. Her work on noise-tolerant zeroing neural networks further extends the robustness of real-time matrix inversion. Through these innovations, Lu has significantly advanced the practical deployment of neural dynamics in robotics and electronics, offering elegant solutions to long-standing challenges in disturbance-prone environments.
Research Focus
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