Model-free adaptive control of shock buffet flow over an airfoil

REN Kai; GAO Chuanqiang; ZHANG Weiwei

doi:10.7638/kqdlxxb-2021.0297

English Version Journal Login

您当前的位置：

首页 >

文章列表页 >

Model-free adaptive control of shock buffet flow over an airfoil

更新时间：2026-05-28

- Model-free adaptive control of shock buffet flow over an airfoil
- Vol. 39, Issue 6, Pages: 149-155(2021)
- 作者机构：
  
  1. 西北工业大学航空学院,西安,710072
  2. 流体力学智能化国际联合研究所,西安,710072
- 作者简介：
- 基金信息：
- DOI：10.7638/kqdlxxb-2021.0297
  CLC： O354;V211.41
- Published：2021
- 稿件说明：
移动端阅览
任凯, 高传强, 张伟伟. 翼型激波抖振的无模型自适应控制[J]. 空气动力学学报, 2021, 39(6): 149−155.

REN Kai, GAO Chuanqiang, ZHANG Weiwei. Model-free adaptive control of shock buffet flow over an airfoil[J]. 2021, 39(6): 149-155.
任凯, 高传强, 张伟伟. 翼型激波抖振的无模型自适应控制[J]. 空气动力学学报, 2021, 39(6): 149−155. DOI： 10.7638/kqdlxxb-2021.0297

REN Kai, GAO Chuanqiang, ZHANG Weiwei. Model-free adaptive control of shock buffet flow over an airfoil[J]. 2021, 39(6): 149-155. DOI： 10.7638/kqdlxxb-2021.0297.

摘要

由于受到流动环境中的不确定因素影响，针对流动系统设计的闭环控制律需要考虑这些不确定因素，自动适应随机扰动和突发扰动。基于流动模型所设计的闭环最优控制，虽然可以以较小的控制量获得满足目标函数的最优控制效果，但随着流动模型的引入，随之而来的建模精度、未建模动态等问题也会出现，固定的流动模型也会限制控制系统的自适应能力。针对翼型在跨声速流动中遇到的激波抖振问题，为了消除不同来流状态的激波抖振带来的脉动载荷，开展了基于数据驱动方法的无模型自适应控制。流场数值仿真采用URANS方法，作动机构采用尾缘舵面，以升力系数作为反馈信号。当流动状态变化时，无模型自适应控制利用输入输出数据在线将流动系统等价转化为动态线性化数据模型，最小化性能指标得到控制律，使系统自动地工作于最优或接近最优的状态。时域仿真结果显示，无模型自适应控制效果优于开环控制和比例控制，并且当来流状态随时间发生变化时，无模型自适应控制也能够完全消除抖振脉动载荷。

Abstract

Due to the existence of various disturbances and uncertainties in complex flow environments

the design of flow control systems needs to consider these uncertainties and to adjust the control law automatically to adapt to random and abrupt disturbances. The closed-loop optimal control based on low-order linear models

which is widely used at present

can obtain the predetermined control effect with a small amount of control input

but the modelling accuracy and the unmodeled dynamics of the reduced-order models can greatly limit the adaptive ability of such control strategies. In this study

aiming at the shock buffet problem of airfoils in transonic flow

a model-free adaptive control (MFAC) based on the data-driven method was carried out to eliminate the fluctuating load caused by the shock buffet in different freestream states. The control uses the unsteady Reynolds Average Navier-Stokes (URANS) method for the flow field simulation

the trailing-edge flap as the actuator

and the lift coefficient as the feedback signal. When the flow state changes

the data-driven MFAC uses the input and output data to convert the flow system into a dynamic linearized data model online and minimizes the performance index to obtain the control law

to make the system automatically work in the optimal or close to the optimal state. The simulation results show that MFAC is better than existing open-loop control and proportional control strategies

and can completely suppress the buffet load even if the freestream state changes.

关键词

Keywords

references

SCOTT COLLIS S, JOSLIN R D, SEIFERT A, et al. Issues in active flow control: theory, control, simulation, and experiment[J]. Progress in Aerospace Sciences, 2004, 40(4-5): 237-289.https://cfwebprod.sandia.gov/cfdocs/CompResearch/docs/pas-flow-ctrl.pdf DOI:10.1016/j.paerosci.2004.06.001

XU C X. Coherent structures and drag-reduction mechanism in wall turbulence[J]. Advances in Mechanics, 2015, 45: 111-140. (in Chinese)doi: 10.6052/1000-0992-15-006

WU C J, WANG L, WU J Z. Suppression of the von Kármán vortex street behind a circular cylinder by a travelling wave generated by a flexible surface[J]. Journal of Fluid Mechanics, 2007, 574: 365-391. DOI:10.1017/s0022112006004150

ZHOU F Q, YANG D G, WANG X S, et al. Effect of leading edge plate on high speed cavity noise control[J]. Acta Aeronautica et Astronautica Sinica, 2018, 39(4): 121812. (in Chinese)doi: 10.7527/S1000-6893.2017.21812

HONG J W, CHEN X D, ZHANG Y L, et al. The primary numerical research of active control technology in flow[J]. Acta Aerodynamica Sinica, 2005, 23(4): 402-407. (in Chinese)

YAO W, JAIMAN R K. Feedback control of unstable flow and vortex-induced vibration using the eigensystem realization algorithm[J]. Journal of Fluid Mechanics, 2017, 827: 394-414. DOI:10.1017/jfm.2017.470

FLINOIS T L B, MORGANS A S. Feedback control of unstable flows: a direct modelling approach using the Eigensystem Realisation Algorithm[J]. Journal of Fluid Mechanics, 2016, 793: 41-78. DOI:10.1017/jfm.2016.111

LECLERCQ C, DEMOURANT F, POUSSOT-VASSAL C, et al. Linear iterative method for closed-loop control of quasiperiodic flows[J]. Journal of Fluid Mechanics, 2019, 868: 26-65. DOI:10.1017/jfm.2019.112

HENNINGSON D S, ÅKERVIK E. The use of global modes to understand transition and perform flow control[J]. Physics of Fluids, 2008, 20(3): 031302. DOI:10.1063/1.2832773

GAO C Q, ZHANG W W, KOU J Q, et al. Active control of transonic buffet flow[J]. Journal of Fluid Mechanics, 2017, 824: 312-351. DOI:10.1017/jfm.2017.344

DADFAR R, HANIFI A, HENNINGSON D S. Control of instabilities in an unswept wing boundary layer[J]. AIAA Journal, 2018, 56(5): 1750-1759. DOI:10.2514/1.j056415

HOU Z S, WANG Z. From model-based control to data-driven control: Survey, classification and perspective[J]. Information Sciences, 2013, 235: 3-35. DOI:10.1016/j.ins.2012.07.014

REN F, WANG C L, TANG H. Active control of vortex-induced vibration of a circular cylinder using machine learning[J]. Physics of Fluids, 2019, 31(9): 093601. DOI:10.1063/1.5115258

ZHOU Y, FAN D W, ZHANG B F, et al. Artificial intelligence control of a turbulent jet[J]. Journal of Fluid Mechanics, 2020, 897: A27. DOI:10.1017/jfm.2020.392

ZHENG C D, JI T W, XIE F F, et al. From active learning to deep reinforcement learning: Intelligent active flow control in suppressing vortex-induced vibration[J]. Physics of Fluids, 2021, 33(6): 063607. DOI:10.1063/5.0052524

DOWELL E H, CRAWLEY E F, CURTISS JR H C, et al. A modern course in aeroelasticity[M]. Springer Netherlands, 2004. doi: 10.1007/1-4020-2106-2

DONG S H, SHI A M, YE Z Y, et al. CFD computation and POD analysis for transonic buffet on a supercritical airfoil[J]. Acta Aerodynamica Sinica, 2015, 33(4): 481-487. (in Chinese)doi: 10.7638/kqdlxxb-2013.0100

WANG X, REN K, GAO C Q, et al. Adaptive control method for frequency lock-in in transonic buffet flow[J]. Acta Aerodynamica Sinica, 2020, 38(5): 1011-1016. (in Chinese)doi: 10.7638/kqdlxxbG2020.0085

SMITH A N, BABINSKY H, FULKER J L, et al. Shock wave/ boundary-layer interaction control using streamwise slots in transonic flows[J]. Journal of Aircraft, 2004, 41(3): 540-546. DOI:10.2514/1.11479

TIAN Y, LIU P Q, PENG J. Using shock control bump to improve transonic buffet boundary of airfoil[J]. Acta Aeronautica et Astronautica Sinica, 2011, 32(8): 1421-1428. (in Chinese)doi: 11-1929/V.20110419.1702.005

HUANG J B, XIAO Z X, LIU J, et al. Simulation of shock wave buffet and its suppression on an OAT15A supercritical airfoil by IDDES[J]. Science China Physics, Mechanics and Astronomy, 2012, 55(2): 260-271. DOI:10.1007/s11433-011-4601-9

高传强. 跨声速复杂气动弹性问题的诱发机理及控制研究[D]. 西安: 西北工业大学, 2018.

ZHANG W W, GAO C Q, YE Z Y. The complex transonic aeroelastic phenomena and it's mechanisms[J]. Chinese Science Bulletin, 2018, 63(12): 1095-1110. (in Chinese)doi: 10.1360/N972018-00151

WANG G, MIAN H H, YE Z Y, et al. Improved point selection method for hybrid-unstructured mesh deformation using radial basis functions[J]. AIAA Journal, 2014, 53(4): 1016-1025. DOI:10.2514/1.J053304

DOERFFER P, HIRSCH C, DUSSAUGE J P, et al. NACA0012 with aileron (marianna braza)[M]//Notes on Numerical Fluid Mechanics and Multidisciplinary Design. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010: 101-131. doi:10.1007/978-3-642-03004-8_4

侯忠生, 金尚泰. 无模型自适应控制: 理论与应用[M]. 北京: 科学出版社, 2013.

GAO C Q, ZHANG W W, YE Z Y. Study on transonic buffet suppression with flapping rudder[J]. Acta Aeronautica et Astronautica Sinica, 2015, 36(10): 3208-3217. (in Chinese)doi: 10.7527/S1000-6893.2015.0034

GAO C Q, ZHANG W W, YE Z Y. Numerical study on closed-loop control of transonic buffet suppression by trailing edge flap[J]. Computers Fluids, 2016, 132: 32-45. DOI:10.1016/j.compfluid.2016.03.031

Views

下载量

CSCD

Alert me when the article has been cited

提交

Tools

Publicity Resources

Numerical simulation of hypersonic magnetofluid control based on non-linear coupling constitutive relation

Influence of slotted track on aerodynamic characteristics of high-speed maglev train

Research status of aerodynamic design for integrated propulsion and airframe in near-space high-altitude long-endurance (HALE) UAVs

Preface to the special column on “UAV Aero-Propulsive Integration Design”

Oblique detonation engine: Initiation and stabilization of oblique detonation waves in confined spaces

Related Author

Shi Hao

Xiao Hong

Zhou Li

Wang Zhanxue

Liu Feng

Yue Si

Wu Xiaolong

Li Xiao

Related Institution

Collaborative Innovation Center for Advanced Aero-Engine, Beijing

School of Power and Energy, Northwestern Polytechnical University, Xi'an

Key Laboratory of Traffic Safety on the Track of Ministry of Education, Central South University, Changsha

China Railway Siyuan Survey and Design Group Co., Ltd, Wuhan

School of Aeronautic Science and Engineering, Beihang University, Beijing

AI问答

⁰