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Control-Oriented Model Reduction for Minimizing Transient Energy Growth in Shear Flows

机译:面向控制的模型简化,可最大程度减少剪切流中的瞬态能量增长

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摘要

A linear nonmodal mechanism for transient amplification of perturbation energy is known to trigger subcritical transition to turbulence in many shear flows. Feedback control strategies for minimizing this transient energy growth can be formulated as convex optimization problems based on linear matrix inequalities. Unfortunately, solving the requisite linear matrix inequality problem can be computationally prohibitive within the context of high-dimensional fluid flows. This paper investigates the utility of control-oriented reduced-order models to facilitate the design of feedback flow control strategies that minimize the maximum transient energy growth. An output projection onto proper orthogonal decomposition modes is used to faithfully capture the system energy. Subsequently, a balanced truncation is performed to reduce the state dimension, while preserving the system's input-output properties. The model reduction and control approaches are studied within the context of a linearized channel flow with blowing and suction actuation at the walls. Controller synthesis for this linearized channel flow system becomes tractable through the use of the proposed control-oriented reduced-order models. Further, the resulting controllers are found to reduce the maximum transient energy growth compared with more conventional linear quadratic optimal control strategies.
机译:已知一种用于扰动能量瞬态放大的线性非模态机制会在许多剪切流中触发从亚临界转变为湍流。可基于线性矩阵不等式将用于最小化此暂态能量增长的反馈控制策略表述为凸优化问题。不幸的是,在高维流体流动的背景下,解决必要的线性矩阵不等式问题在计算上是令人望而却步的。本文研究了面向控制的降阶模型在简化最小化最大瞬态能量增长的反馈流控制策略设计中的实用性。在正确的正交分解模式上的输出投影用于忠实地捕获系统能量。随后,执行平衡截断以减小状态维,同时保留系统的输入输出属性。在线性化通道流动的情况下研究了模型的简化和控制方法,并在壁上进行了吹气和吸气驱动。通过使用建议的面向控制的降阶模型,用于此线性化通道流系统的控制器综合变得易于处理。此外,发现与更常规的线性二次最优控制策略相比,所得的控制器减少了最大瞬态能量增长。

著录项

  • 来源
    《AIAA Journal》 |2020年第3期|1034-1045|共12页
  • 作者

  • 作者单位

    Univ Minnesota Aerosp Engn & Mech Minneapolis MN 55455 USA;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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