|本期目录/Table of Contents|

改进极大似然法动力调谐陀螺仪闭环辨识(PDF)

《纳米技术与精密工程》[ISSN:1672-6030/CN:12-1351/O3]

期数:
2017年6期
页码:
499-506
栏目:
出版日期:
2017-11-15

文章信息/Info

Title:
Dynamically Tuned Gyroscope Closed-Loop Identification Based on Modified Maximum Likelihood Method
文章编号:
1672-6030(2017)06-0499-08
作者:
王亚辉1 李醒飞12 纪越1 赵建远1
1. 天津大学精密仪器与光电子工程学院, 天津 300072; 2. 精密测试技术及仪器国家重点实验室(天津大学), 天津 300072
Author(s):
Wang Yahui1 Li Xingfei12 Ji Yue1 Zhao Jianyuan1
1. School of Precision Instrument and OptoElectronics Engineering, Tianjin University, Tianjin 300072, China; 2. State Key Laboratory of Precision Measuring Technology and Instruments (Tianjin University), Tianjin 300072, China
关键词:
闭环辨识 动力调谐陀螺仪 极大似然法 有色噪声
Keywords:
closed-loop identification dynamically tuned gyroscope maximum likelihood method colored noise
分类号:
TP273; U666
DOI:
10.13494/j.npe.20160005
文献标识码:
A
摘要:
针对Box-Jenkins(BJ)模型辅助向量法和Newton-Raphson法计算繁杂、收敛速度慢、辨识精度不高等问题和极大似然法无法直接应用在闭环辨识的限制,把结合BJ模型的递推的极大似然(recursive maximum likelihood,RML)参数估计法应用于动力调谐陀螺仪的闭环辨识,提出了不受耦合有色噪声影响的BJ模型近似递推极大似然(BJRML)闭环辨识法,获取了动力调谐陀螺仪的参数估计值并实现陀螺仪在线性能监测.结合动力调谐陀螺仪的闭环简化模型等先验知识,通过数值仿真验证BJRML法辨识结果的无偏一致性与渐进最优性;在实验室条件下采用本方法进行动力调谐陀螺仪闭环辨识实验.仿真结果表明:在有色噪声存在的条件下,BJRML法的辨识结果是一致无偏渐进最优的;闭环辨识实验结果表明:辨识精度优于92%;辨识结果能够跟踪陀螺特性,基本实现陀螺仪性能在线监测.
Abstract:
Regarding the problems that Box-Jenkins instumental variable (BJIV) method is slow in convergence speed, that Newton-Raphson method is low in precision, and that maximum likelihood method cannot be directly applied in closedloop identification, Box-Jenkins recursive maximum likelihood (BJRML) method was proposed and applied to dynamically tuned gyroscope (DTG) closed-loop identification. DTG model parameter was obtained, and online performance monitoring was achieved. The method combined BoxJenkins model with recursive maximum likelihood method. Also, it is not affected by coupling colored noise. Firstly, the prior knowledge of simplified closedloop model of DTG was obtained. Then, the paper verified the unbiased consistency and asymptotic optimality of BJRML identification results. Finally, identification experiments were conducted on the DTG closed-loop system in laboratory. The simulation results are as follows: the estimations of BJRML method are unbiased and consistent with different noise levels, and the asymptotic variance is near-optimal. Experiment results show that the identification fitting degree is more than 92%. Identification results can track gyroscope characteristics and achieve basic online monitoring.

参考文献/References

备注/Memo

备注/Memo:
收稿日期: 2016-03-25. 基金项目: 国家自然科学基金资助项目(60972129);国家重点实验室开放基金资助项目(pil1006). 作者简介: 王亚辉(1989—),男,硕士研究生. 通讯作者: 李醒飞,教授,lixf@tju.edu.cn.
更新日期/Last Update: 2017-12-21