| 暂冲式高速风洞流场控制系统建模与仿真 |
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| 引用本文： | 芮伟,杜宁,袁平,易凡,金志伟. 暂冲式高速风洞流场控制系统建模与仿真[J]. 实验流体力学, 2015, 0(6): 89-95. DOI: 10.11729/syltlx20140074 |
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| 作者姓名： | 芮伟 杜宁 袁平 易凡 金志伟 |
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| 作者单位： | 中国空气动力研究与发展中心,四川 绵阳,621000 |
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| 摘 要： | 为满足中国空气动力研究与发展中心的2.4m跨声速风洞流场品质改进的需要,有必要建立一个高效的风洞流场控制模型作为控制器设计的验证平台。由于难以建立精确的空气动力学模型,且2.4m 跨声速风洞长期运行积累了大量的试验运行数据的实际,数据建模成为建模方法的首选。在硬件上,建立了基于反射内存技术的流场控制仿真系统,以获取现场采集的数据。建模方法采用数据建模方式,主要是利用系统辨识理论,将整个系统看成是一个“黑箱”,利用现场采集的数据来确定系统的参数和输入输出间的映射关系。采用以非线性自回归滑动平均模型(Non-linear Auto-Regressive Moving Average Model with Exogenous Inputs,NARMAX)作为风洞系统的数据模型,应用互信息法、曲线拟合法和伪最近邻点法分别确定了模型中采样间隔、时间滞后以及阶次3个参数。对比了最小二乘线性回归、BP 神经网络以及最小二乘支持向量机(LSSVM)3种方法对模型的拟合效果,确立了最小二乘支持向量机作为最终的拟合方法。为了提高仿真的精度,根据风洞运行的特点,将其整个过程划分为冲压、启动和调节3个阶段,分别建立了各个阶段的子模型。由于风洞系统是一个多输入多输出系统,并且延迟和阶次较大,采用了基于信息熵的数据压缩方法,实现了简化子模型规模的目的。最后,采用多模型融合的方法将各个阶段的子模型通过加权的方法来完成融合,从而构建起整个风洞系统的模型。稳定段总压和驻室静压分别通过所建模型得到,最后通过马赫数的计算公式得到试验段马赫数值。仿真结果表明:所建模型在运行包络线范围内的试验工况下,总压预测精度达到0.1%、马赫数预测精度基本达到0.001,达到了研究的目的。该项工作的开展较为系统地建立了暂冲式风洞的流场控制模型,建立的模型将为下一阶段基于现代控制理论的控制器设计奠定基础。
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| 关 键 词： | NARMAX模型 互信息法 伪最近邻点法 最小二乘支持向量机 跨声速风洞 |
Modeling and simulation of flow field control system in intermittent transonic wind tunnel |
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| Abstract: | To improve the flow field quality of the 2 .4m transonic wind tunnel in CARDC,it is necessary to build an efficient flow field control model for controller design verification plat-form of the wind tunnel.The data driven modeling method becomes an important alternative because accurate aerodynamic models are difficult to establish while a lot of experimental data have been accumulated in the long running of the 2.4m wind tunnel.As to the hardware,a flow field control simulation system is established based on the memory reflective technology to get the measurement data in situ.The data driven modeling method is adopted based on the system identification theory,which regards the system as a “black box”and establishes the relationship between the inputs and the outputs by algorithms using the data obtained from the actual meas-urements.Non-linear Auto-Regressive Moving Average Model with Exogenous Inputs (NAR-MAX)model is selected as the wind tunnel’s data model.Mutual information algorithm,curve fitting algorithm and false nearest neighbors algorithm are respectively used to identify sampling interval,time delay and order.The effects of least square linear regression,BP neural network and supporting vector machine (LS SVM)on model fitting are compared,and LS SVM is cho-sen.To improve the precision of simulation,the running process of wind tunnel can be divided into three stages:charging stage,start-up stage and adjusting stage according to respective run-ning features and then each stage is modeled separatedly.Due to the MIMO features,large time delay and high order characteristics of the wind tunnel,a data compression method based on in-formation entropy is adopted which scales down the model.Finally,the model for the whole run-ning process is realized by fusing the sub-models of the three stages.The total pressure at stag-nation and the static pressure at test section are calculated via the model and the Mach number can be obtained by the relationship between the pressure and Mach number.The simulation re-sults show that within the scope of the test conditions,the total pressure prediction precision of the model reaches 0.1%,and the Mach number prediction precision generally reaches 0.001.The goal has been attained.In conclusion,an intermittent transonic wind tunnel flow field control model is systematically established,which will play a significant role in the future design of the controller based on the modern control theory. |
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