期刊
IET CONTROL THEORY AND APPLICATIONS
卷 5, 期 14, 页码 1648-1657出版社
INST ENGINEERING TECHNOLOGY-IET
DOI: 10.1049/iet-cta.2010.0416
关键词
-
资金
- Shandong Provincial Natural Science Foundation [ZR2010FM024]
- Shandong Province Higher Educational Science and Technology Program [J10LG12]
- Postdoctoral Innovation Program Foundation of Shandong Province of China [201002002]
For parameter estimation of output error moving average (OEMA) systems, this study combines the auxiliary model identification idea with the filtering theory, transforms an OEMA system into two identification models and presents a filtering and auxiliary model-based recursive least squares (F-AM-RLS) identification algorithm. Compared with the auxiliary model-based recursive extended least squares algorithm, the proposed F-AM-RLS algorithm has a high computational efficiency. Moreover, a filtering and auxiliary model-based least squares iterative (F-AM-LSI) identification algorithm is derived for OEMA systems with finite measurement input-output data. Compared with the F-AM-RLS approach, the proposed F-AM-LSI algorithm updates the parameter estimation using all the available data at each iteration, and thus can generate highly accurate parameter estimates.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据