首页 | 本学科首页   官方微博 | 高级检索  
     检索      

广义随机2-D系统的状态估计
引用本文:盛梅,邹云.广义随机2-D系统的状态估计[J].南京理工大学学报(自然科学版),2004,28(2):128-131.
作者姓名:盛梅  邹云
作者单位:南京理工大学,自动化系,江苏,南京,210094
基金项目:国家自然科学基金项目 (6 0 0 74 0 0 7)
摘    要:考虑广义随机2-D系统的卡尔曼估计问题。目的是利用最小方差准则,在系统同时受到动态噪声和测量噪声干扰下,得到一类2-D系统的卡尔曼滤波。通过运用斜割支线和几何方法,给出状态向量的卡尔曼滤波与最优预测。同时,给出滤波和预测误差的方差与协方差阵的显示公式。

关 键 词:2-D系统  广义系统  随机系统  卡尔曼滤波  预测
文章编号:1005-9830(2004)02-0128-04
修稿时间:2002年10月25

State Estimation of Singular Stochastic 2-D System
SHENG Mei,ZOU Yun.State Estimation of Singular Stochastic 2-D System[J].Journal of Nanjing University of Science and Technology(Nature Science),2004,28(2):128-131.
Authors:SHENG Mei  ZOU Yun
Abstract:The problem of Kalman filtering is considered for stochastic signular secondary 2-D Fornasini-Marchesini Models (2-D SFMMII) subjected to white noises in both the state and measurement equations. The aim is to design a kind of 2-D Kalman filter to ensure the minimum variances of the filtering error system for all admissible noises. A sufficient condition for the solvability of the problem is obtained. The desired filter can be constructed by using the cross-cut and geometry method. The optimum prediction of the state vector is also given. The explicit formulae are provided for the variance matrices and covariance matrices of the filtering and prediction problems.
Keywords:2-D system  singular system  stochastic system  Kalman filtering  prediction
本文献已被 CNKI 维普 万方数据 等数据库收录!
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号