Designs of Feedback Controllers for Fluid Flows Based On Model Predictive Control and Regression Analysis
Designs of Feedback Controllers for Fluid Flows Based On Model Predictive Control and Regression Analysis
复制标题
基于模型预测控制和回归分析的流体流动反馈控制器设计
作者：
Yasuo Sasaki;Daisuke Tsubakino
在线计算的复杂性是模型预测控制（MPC）的缺点，将其应用于Navier -Stokes方程，以减少计算复杂性，我们提出了一种使用回归分析的方法来近似MPC ，我们提取了两个国家反馈控制法律和两个圆柱围绕基准的输出反馈控制定律。通过脊回归提取了不同的数量，而两个输出反馈控制定律（其测量结果是表面压力）是通过脊回归和高斯过程回归提取的。为了完全抑制涡流的脱落，而输出反馈控制定律无法完全抑制漩涡此外，我们确认这些控制定律对雷诺数的变化具有一定程度的鲁棒性。
Complexity of online computation is a drawback of model predictive control (MPC) when applied to the Navier–Stokes equations. To reduce the computational complexity, we propose a method to approximate the MPC with an explicit control law by using regression analysis. In this paper, we extracted two state-feedback control laws and two output-feedback control laws for flow around a cylinder as a benchmark. The state-feedback control laws that feed back different quantities to each other were extracted by ridge regression, and the two output-feedback control laws, whose measurement output is the surface pressure, were extracted by ridge regression and Gaussian process regression. In numerical simulations, the state-feedback control laws were able to suppress vortex shedding almost completely. While the output-feedback control laws could not suppress vortex shedding completely, they moderately improved the drag of the cylinder. Moreover, we confirmed that these control laws have some degree of robustness to the change in the Reynolds number. The computation times of the control input in all the extracted control laws were considerably shorter than that of the MPC.