[1]王一清,黄惟一,崔建伟,等.基于Kalman滤波的一阶微分参量估计方法的研究[J].东南大学学报(自然科学版),2004,34(1):25-27.[doi:10.3969/j.issn.1001-0505.2004.01.006]
 Wang Yiqing,Huang Weiyi,Cui Jianwei,et al.Research on one-order differential coefficient estimation based on Kalman filtering[J].Journal of Southeast University (Natural Science Edition),2004,34(1):25-27.[doi:10.3969/j.issn.1001-0505.2004.01.006]
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基于Kalman滤波的一阶微分参量估计方法的研究()
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《东南大学学报(自然科学版)》[ISSN:1001-0505/CN:32-1178/N]

卷:
34
期数:
2004年第1期
页码:
25-27
栏目:
机械工程
出版日期:
2004-01-20

文章信息/Info

Title:
Research on one-order differential coefficient estimation based on Kalman filtering
作者:
王一清 黄惟一 崔建伟 宋爱国
东南大学仪器科学与工程系, 南京 210096
Author(s):
Wang Yiqing Huang Weiyi Cui Jianwei Song Aiguo
Department of Instrument Science and Technology, Southeast University, Nanjing 210096, China
关键词:
微分参量估计 噪声抑制 Kalman滤波 腕力传感器
Keywords:
differential coefficient estimation denoising Kalman filter wrist transducer
分类号:
TH701;TP241
DOI:
10.3969/j.issn.1001-0505.2004.01.006
摘要:
基于迭代Kalman滤波算法,提出了一种微分参量的估计方法,并将其应用于腕力传感器的一阶力微分信号的提取处理中.通过对观测信号建立AR模型和递推的使用Kalman滤波算法,有效地抑制了噪声强度从而提高了微分参量的计算精度,克服了直接计算法误差较大的缺点,同时还避免了因加装速度传感器而对原腕力传感器动态性能造成的影响.文中讨论了在均匀分布的背景噪声下如何估计原始信号的一阶微分参量的问题,并给出了仿真结果.试验表明该方法具有良好的计算精度和较强的收敛性.
Abstract:
Based on iteration of the Kalman filter, a method is proposed to estimate the differential coefficient and to be applied to get the one-order differential coefficient from a wrist transducer. Through constructing an AR model of measured signal and recursive employment of the Kalman filter, the strength of background noise is effectively controlled, so the computation accuracy is attained and the serious error of the direct computation method is overcome. Meanwhile, as will eliminate the influence on dynamic performance of wrist transducer due to surplus apparatus. The problem of how to extract differential information from the signal contaminated by uniform distribution noise is discussed and experimental results are presented. The experiment shows that a high performance and robustness can be achieved by this method.

参考文献/References:

[1] Yang Wenqiang,Jia Zhengchun,Xu Qiang.Speed sensorless vector control of induction motor based on reduced order extended Kalman filter [J].Journal of Southeast University,2001,117(1):41-45.
[2] Cowan C F N,Grant P M.自适应滤波器[M].邵祥义等译.上海:复旦大学出版社,1990.21-26.
[3] 邓自立.卡尔曼滤波与维纳滤波[M].哈尔滨:哈尔滨工业大学出版社,2001.262-274.
[4] 杨叔子,吴雅.时间序列分析的工程应用[M].武汉:华中理工大学出版社,1989.41-57.
[5] King J Thomas.数值计算引论[M].林成森等译.南京:南京大学出版社,1998.304-311.

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备注/Memo

备注/Memo:
基金项目: 国家高技术研究发展计划(863计划)资助项目(2001AA423140).
作者简介: 王一清(1973—), 男, 博士生; 黄惟一(联系人), 男, 教授, 博士生导师, hhwy@seu.edu.cn.
更新日期/Last Update: 2004-01-20