Robust least square method and its application to parameter estimation

被引：0
|
作者：
Zhang Mei [1 ]
Zhang Chenghui [1 ]
Zhang Huanshuil [1 ]
Cui Peng [1 ]
Du Yanchun [1 ]
机构：
[1] Shandong Univ, Sch Control Sci & Engn, Jinan 250010, Peoples R China
来源：
2007 IEEE INTERNATIONAL CONFERENCE ON AUTOMATION AND LOGISTICS, VOLS 1-6 | 2007年
关键词：
robust least square method (RLS); parameter estimation; robustness;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
The system identification problem is researched when the input and output signal are both corrupted by noise. The robust least square (RLS) method and its application to parameter estimation problem, in which the perturbations are unknown but bounded (UBB), are introduced. The method can be interpreted as Tikhonov regularization procedure, with the advantage that it provides an exact bound on the robustness of solution and a rigorous way to compute the regularization parameter. Simulation results verify that the estimation precision and the robustness anti-noise of RLS are remarkably higher than other method when the input and output signal are both corrupted by noise.
引用
收藏
页码：1483 / 1486
页数：4
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