Xuyang Lou
Papers
2
Total Citations
10
H-Index
2
About
Xuyang Lou is a control systems researcher whose work bridges adaptive neural network control and hybrid systems theory, with a focus on real-world engineering applications. His most cited paper, "Adaptive neural network based boundary control of a flexible marine riser system with output constraints" (2022, 7 citations), addresses a critical challenge in offshore engineering: suppressing vibrations in flexible risers subject to unknown nonlinear disturbances and output constraints. By developing a boundary control method that leverages adaptive neural networks, Lou provides a practical solution for maintaining structural integrity in deep-sea environments. His second notable work, "Reset control and ℒ₂-gain analysis of piecewise-affine systems" (2023, 3 citations), advances hybrid control theory by establishing stability conditions for piecewise-affine systems under dynamic state-feedback control, using bilinear matrix inequality conditions. This contribution is significant for systems that switch between multiple operating modes, such as in robotics or power electronics. Lou’s research demonstrates a rare ability to combine rigorous theoretical analysis with tangible engineering impact, making his work valuable for both control theorists and practitioners in marine and industrial automation.
Research Focus
Key Achievements
Top Papers
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- 2