摘要
鉴于激光陀螺温度误差模型的非线性和时变性,从提高模型辨识质量的需要出发,运用基于最小概率DWO(直接加权优化)的非线性系统辨识方法进行激光陀螺温度误差模型辨识研究,提出了一种精度更高的激光陀螺温度误差模型。该模型以带宽作为唯一需要确定的模型参数,避免了以往温度误差模型研究中的结构与参数辨识等复杂问题,从而在保证模型辨识质量的基础上,也相应提高了模型的适应能力,并通过两种温度误差特性有显著区别的激光陀螺(四频差动激光陀螺和二频机抖激光陀螺)的温度实验数据验证了该模型的正确性和适应性。
In view of the non-linearity and time variability in temperature error model of laser gyro, the DWO (Direct Weight Optimization) based on minimal probability was applied to study the identification method of temperature error model for laser gyro to improve the identification model quality, and a laser gyro temperature error model with higher accuracy was presented. The model proposed uses bandwidth as its only model parameter that need to be determined. This avoids some complex problems, such as model structure identification, model parameters identification, so the available ability of model is improved in the premise of guaranteeing the model quality. The model proposed is validated by a large amount of temperature test data from the four-frequency differential laser gyro and the two-frequency dithered ring laser gyro which have significant differences in temperature error characteristics.
出处
《中国惯性技术学报》
EI
CSCD
2008年第5期618-622,共5页
Journal of Chinese Inertial Technology
基金
国家973重大基础研究项目资助(61384010303)
关键词
非线性系统辨识
直接加权优化
最小概率
激光陀螺
温度误差
nonlinear system identification
direct weight optimization
minimal probability
laser gyro
temperature error