改进极大似然法动力调谐陀螺仪闭环辨识  

Dynamically Tuned Gyroscope Closed-Loop Identification Based on Modified Maximum Likelihood Method

作　　者：王亚辉[1] 李醒飞[1,2] 纪越 赵建远[1] 

机构地区：[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

出　　处：《纳米技术与精密工程》2017年第6期499-506,共8页Nanotechnology and Precision Engineering

基　　金：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)

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.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 characteristicsand achieve basic online monitoring.

关 键 词：闭环辨识 动力调谐陀螺仪 极大似然法 有色噪声 

分 类 号：TN96[电子电信—信号与信息处理]