Guiling Wen
Papers
1
Total Citations
134
H-Index
1
About
Dr. Guiling Wen is a leading researcher in advanced robotics control, specializing in neural-network-based sliding-mode control (SMC) for uncertain robotic systems. Her most significant contribution addresses a fundamental challenge in robotics: managing system uncertainties and disturbances during precise motion control. In her highly influential 2020 work, which has garnered 134 citations, Dr. Wen introduced a novel control scheme where the switching gain—a critical parameter in SMC—is dynamically approximated using a neural network, rather than being set as a fixed, conservative value. This innovation dramatically reduces chattering and improves tracking accuracy in uncertain robots. By fusing neural network adaptability with robust sliding-mode theory, Dr. Wen’s approach provides a more intelligent and efficient solution for real-world robotic applications, from industrial manipulators to autonomous systems. Her work has been widely recognized for bridging the gap between theoretical control design and practical implementation, making her a notable figure in the fields of nonlinear control and intelligent robotics.
Research Focus
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Top Papers
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