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时变系统的Laguerre模型辨识及设计变量(2) ——Kalman滤波法
引用本文:丁肇红,沙泉,袁震东.时变系统的Laguerre模型辨识及设计变量(2) ——Kalman滤波法[J].华东师范大学学报(自然科学版),2003,2003(1):25-30.
作者姓名:丁肇红  沙泉  袁震东
作者单位:1. 上海应用技术学院,自动化系,上海,200233
2. 华东师范大学,数学系,上海,200062
摘    要:文章考虑动态线性系统的时变参数是平稳的AR(1)变量,系统为时变的Laguerre模型时的传递函数估计的均方误差(MSE)。在缓慢时变和高阶模型下,利用Kalman滤波算法,得到MSE的近似表达式。最后得到了Kalman滤波算法的设计变量的最优解。

关 键 词:时变系统  MSE  Laguerre模型  设计变量  时变系统  MSE  Laguerre模型  设计变量
文章编号:1000-5641(2003)01-0025-06
收稿时间:2001-6-12
修稿时间:2001年6月1日

Identification of Laguerre Model and Design Variable for Time-varying Systems(2) ------Kalman filter algorithms
DING Zhao-hong,SHA Quan,YUAN Zhen-dong.Identification of Laguerre Model and Design Variable for Time-varying Systems(2) ------Kalman filter algorithms[J].Journal of East China Normal University(Natural Science),2003,2003(1):25-30.
Authors:DING Zhao-hong  SHA Quan  YUAN Zhen-dong
Institution:1. Department of Automation, Shanghai College of Applied Technology, Shanghai 200233, China; 2. Department of Mathematics, East China Normal University, Shanghai 200062. China
Abstract:It is supposed that the time-varying parameters included in the system are stationary AR(1) variable. The estimate of the mean square error (MSE) of transfer function for time-varying Laguerre model is discussed. The approximate expression of MSE for Kalman filter algorithms can be derived under following assumptions:the dynamic of the system is slowly changing, the adaptation is also quite slow and the order of model system is high enough. Using Laguerre model instead of FIR model,the MSE will be reduced and the order of Laguerre model is reduced as well. The optimization problems for design variables of time-varying system identification algorithms are discussed.
Keywords:time-varying system  MSE  laguerre model  kalman filter algorithms  design variable
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