动力调谐陀螺仪子空间辨识

赵建远; 李醒飞; 田凌子

doi:10.3788/OPE.20152302.0423

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动力调谐陀螺仪子空间辨识

微纳技术与精密机械 | 更新时间：2020-08-13

- 动力调谐陀螺仪子空间辨识
- Subspace identification for dynamically tuned gyroscope
- 光学精密工程 2015年23卷第2期页码：423-429
- 作者机构：
  
  天津大学精密测试技术及仪器国家重点实验室天津,300072
- 作者简介：
- 基金信息：
  
  精密测试技术及仪器国家重点实验室开放基金资助项目(No.pi11006)();国家自然科学基金资助项目(No.60972129)()
- DOI：10.3788/OPE.20152302.0423
  中图分类号： U666.123;TP273
- 收稿日期：2014-06-05，
  
  修回日期：2014-08-14，
  
  纸质出版日期：2015-02-25
- 稿件说明：
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赵建远, 李醒飞, 田凌子. 动力调谐陀螺仪子空间辨识[J]. 光学精密工程, 2015,23(2): 423-429

ZHAO Jian-yuan, LI Xing-fei, TIAN Ling-zi. Subspace identification for dynamically tuned gyroscope[J]. Editorial Office of Optics and Precision Engineering, 2015,23(2): 423-429
赵建远, 李醒飞, 田凌子. 动力调谐陀螺仪子空间辨识[J]. 光学精密工程, 2015,23(2): 423-429 DOI： 10.3788/OPE.20152302.0423.

ZHAO Jian-yuan, LI Xing-fei, TIAN Ling-zi. Subspace identification for dynamically tuned gyroscope[J]. Editorial Office of Optics and Precision Engineering, 2015,23(2): 423-429 DOI： 10.3788/OPE.20152302.0423.

摘要

针对传统子空间辨识法(SIM)用于动力调谐陀螺仪(DTG)建模过程中存在的结构参数复杂、干扰因素未知、建模精度不高等问题

提出了一种改进的子空间辨识方法。首先

确定辨识对象DTG的状态空间模型集

分析DTG输出信号中存在的固有有色噪声。然后

针对有色噪声的干扰问题

对传统SIM进行改进

通过数据Hankel矩阵的正交投影消除传统SIM的有偏性。最后

在数值仿真中引入置信椭圆

对改进算法进行统计特性分析。仿真结果表明:在不同强度有色噪声干扰下

改进算法无偏

方差特性与有色噪声强度和数据长度有关。辨识实验表明:改进SIM的辨识效果明显优于传统SIM

辨识拟合度优于90%。得到的结果显示改进算法能够应用于DTG系统建模。

Abstract

To deal with the problems of complex structure parameters

unknown interference factors and lower modeling precision in the Dynamically Tuned Gyroscope (DTG) mechanism modeling by the traditional Subspace Identification Method(SIM)

an improved SIM was proposed. Firstly

the DTG state space model sets were determined and DTG inherent colored noises were discussed. Then

the traditional SIM were modified for the colored noise problem and the orthogonal projection of a data Hankel matrix was used to eliminate the SIM bias of traditional method. Finally

a confidence ellipse was introduced in the numerical simulation to analyze the statistics feature of the modified algorithm. Simulation results indicate that the identified results of modified algorithm are unbiased at different colored noise influences

and the variance is related to the noise strength and data length. The identification experiments show that the identification performance of modified SIM is apparently better than that of the traditional SIM

and the identification fitting degree is more than 90%

which means that the modified algorithm is suitable for the DTG system modeling.

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Keywords

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