动力调谐陀螺仪子空间辨识

Subspace identification for dynamically tuned gyroscope

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。

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.