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风洞系统非线性块状结构模型
引用本文:张廷丰,毛志忠,袁平.风洞系统非线性块状结构模型[J].控制理论与应用,2016,33(4):413-421.
作者姓名:张廷丰  毛志忠  袁平
作者单位:东北大学,东北大学,东北大学
基金项目:国家自然科学基金项目(61333006)资助.
摘    要:本文将非线性块状模型的建模思想引入风洞系统模型的建立过程中,针对主排气阀和栅指电液伺服机构具有死区非线性特性,分别用含有死区输入的Hammerstein块状模型描述其动态特性,将主排气阀和栅指机构的输出作为风洞流场的输入,建立两输入两输出多变量耦合动态模型.两个独立的Hammerstein子模型与线性动态耦合的风洞流场模型串联构成一个非线性多变量块状模型.采用自适应加权递推辨识算法在线辨识Hammerstein子模型参数,采用带有遗忘因子的递推最小二乘法辨识风洞流场模型参数.仿真与风洞现场测试结果验证了本文方法的有效性.

关 键 词:风洞系统  块状模型  Hammerstein模型  多变量耦合模型  递推参数辨识
收稿时间:2015/6/25 0:00:00
修稿时间:2015/11/14 0:00:00

Modeling of wind tunnel system based on nonlinear block-oriented model
ZHANG Ting-feng,MAO Zhi-zhong and YUAN Ping.Modeling of wind tunnel system based on nonlinear block-oriented model[J].Control Theory & Applications,2016,33(4):413-421.
Authors:ZHANG Ting-feng  MAO Zhi-zhong and YUAN Ping
Affiliation:Northeastern University,Northeastern University,Northeastern University
Abstract:The nonlinear block-oriented model is applied to describe the wind tunnel system in this paper. Both of the main exhaust valve and the chock finger are modeled by the Hammerstein block-oriented models with dead-zone input in consideration of the dead-zone characteristic in the electro-hydraulic servo mechanism. The wind tunnel flow field is described by a 2 x 2 multi-input multi-output coupling dynamic model. The inputs of the model are the positions of the main exhaust valve and the chock finger, and the outputs are the total pressure and the Mach number. Thus, the nonlinear multivariable block-oriented model of the wind tunnel is composed of two parallel Hammerstein models in series with a linear dynamic coupling model. The adaptive weighted recursive identification method is used to identify the Hammerstein model parameters, while the forgetting factor recursive least squares method is applied to identify the wind tunnel flow field model parameters. Results of simulation and wind tunnel experiments show the validity of the proposed method.
Keywords:wind tunnel system  block-oriented model  Hammerstein model  multivariable coupling model  recursive parameter estimation
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