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A Learning-Based Closed-Loop Fluid Flow Regulation

delete2026-02-28
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OA
AI
M
Mahmut Reyhanoglu *
M
Mohammad Jafari
DOI：10.3390/electronics15050953delete
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摘要

摘要

En 中文
本文提出了一种基于学习的鲁棒控制策略，用于流体流动动态系统，旨在补偿闭环主动流动控制应用中固有的模型不确定性和未知扰动。该方法基于非线性控制理论，并采用梯度下降学习规则来持续更新控制参数和扰动估计。所得闭环系统能够实现鲁棒调节，同时在实施和分析两方面保持简洁性和可解释性。进行了数值仿真以验证该方法的可行性。
Keyword:
learning
flow control
robustness
uncertainty
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期刊

Electronics 封面图
Electronics
IF:
2.6
论文数:
9.8K
被引数:
4.7W

机构

C
columbus state university
学者数:
7
论文数: 5
被引数: 0
W
wentworth institute of technology
学者数:
4
论文数: 5
被引数: 0
引用论文

引用论文

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