SIMO系统辅助变量最小二乘盲辨识方法

Journal of Systems Engineering and Electronics ›› 2009, Vol. 31 ›› Issue (4): 905-910.

SIMO系统辅助变量最小二乘盲辨识方法

陈慧波, 丁锋

江南大学控制科学与工程研究中心, 江苏, 无锡, 214122

收稿日期:2007-12-05 修回日期:2008-03-01 出版日期:2009-04-20 发布日期:2010-01-03
作者简介:陈慧波(1982- ),男,硕士研究生,主要研究方向为系统盲辨识方法.E-mail:chpe2008@sohu.com
基金资助:
国家自然科学基金(60574051);江苏省自然科学基金(BK2007017);江南大学创新团队发展计划资助课题

Instrumental variable least squares blind identification for SIMO systems

CHEN Hui-bo, DING Feng

Control Science and Engineering Research Center, Jiangnan Univ., Wuxi 214122, China

Received:2007-12-05 Revised:2008-03-01 Online:2009-04-20 Published:2010-01-03

摘要/Abstract

摘要： 辅助变量辨识方法是一类重要的辨识方法,然而对于盲辨识,系统输入未知,辅助矩阵的选择就成了难题。针对盲辨识领域研究最多的单输入多输出(SIMO)系统,利用辅助变量方法研究相应的盲辨识方法,其基本思想是联立其中两个子系统进行辨识,利用其他子系统的输出来构造辅助矩阵,从而提出了辅助变量最小二乘盲辨识方法,来获得系统参数估计。还给出所提算法的递推形式,并进行了收敛性分析。仿真例子验证了所提方法的有效性。

Abstract: As an important identification method,the instrumental variable method can give the unbiased parameter estimation for systems with colored noises and unknown noise models.The key is how to choose the instrumental variables to generate the instrumental matrices.In the traditional identification approaches with known input signals,the instrumental variables/matrices are formed by using the inputs,but for blind system identifcation,difficulty arises in that the system inputs are unavailable.For single-input,multi-input systems,this paper studies the corresponding blind identification methods using the instrumental variable technique.The basic idea is to identify two combined subsystems simultaneously using the outputs of the third subsystem as the instrumental variables/matrices and presents the instrunmental variable least squares(IVLS) blind identification algorithm and its recursive form.The convergence of the algorithm is also analyzed.A simulation example is included.

中图分类号:

TP273

陈慧波, 丁锋. SIMO系统辅助变量最小二乘盲辨识方法[J]. Journal of Systems Engineering and Electronics, 2009, 31(4): 905-910.

CHEN Hui-bo, DING Feng. Instrumental variable least squares blind identification for SIMO systems[J]. Journal of Systems Engineering and Electronics, 2009, 31(4): 905-910.

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