Feedback control of transitional shear flows: sensor selection for performance recovery
Feedback control of transitional shear flows: sensor selection for performance recovery
复制标题
过渡剪切流的反馈控制：性能恢复的传感器选择
DOI：
10.1007/s00162-022-00616-z
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发表时间：
2022
影响因子：
3.4
通讯作者：
Hemati, Maziar S.
中科院分区：
文献类型：
--
作者：
Yao, Huaijin;Sun, Yiyang;Hemati, Maziar S.
传感器和致动器的选择和放置是决定使用反馈控制可以实现的性能的重要因素。在控制过渡性流动的情况下，这一决定特别重要，但也很困难。线性化Navier-Stokes方程的高度非正态性使得流动对小扰动敏感，对闭环流动控制具有潜在的剧烈性能后果。全信息控制器，如线性二次型调节器（LQR），已经证明了一些成功的减少瞬态能量增长和抑制过渡，但是，基于传感器的输出反馈控制器具有可比的性能一直难以实现。在这项研究中，我们提出了两种方法，使传感器为基础的输出反馈控制器恢复全信息控制性能的传感器选择：一个基于稀疏控制器的合成方法，和一个基于平衡截断模型简化过程。这两种方法进行了研究内的线性和非线性模拟的亚临界通道流与吹吸驱动的墙壁。我们发现，这两种方法确定的传感器配置允许基于传感器的静态输出反馈LQR控制器恢复全信息LQR控制性能，无论是在减少瞬态能量增长和抑制过渡。此外，我们的研究结果表明，无论是传感器的选择方法和所得的控制器表现出鲁棒性雷诺数的变化。图形摘要
The choice and placement of sensors and actuators is an essential factor determining the performance that can be realized using feedback control. This determination is especially important, but difficult, in the context of controlling transitional flows. The highly non-normal nature of the linearized Navier–Stokes equations makes the flow sensitive to small perturbations, with potentially drastic performance consequences on closed-loop flow control. Full-information controllers, such as the linear quadratic regulator (LQR), have demonstrated some success in reducing transient energy growth and suppressing transition; however, sensor-based output feedback controllers with comparable performance have been difficult to realize. In this study, we propose two methods for sensor selection that enable sensor-based output feedback controllers to recover full-information control performance: one based on a sparse controller synthesis approach, and one based on a balanced truncation procedure for model reduction. Both approaches are investigated within linear and nonlinear simulations of a sub-critical channel flow with blowing and suction actuation at the walls. We find that sensor configurations identified by both approaches allow sensor-based static output feedback LQR controllers to recover full-information LQR control performance, both in reducing transient energy growth and suppressing transition. Further, our results indicate that both the sensor selection methods and the resulting controllers exhibit robustness to Reynolds number variations.Graphic abstract
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