An auxiliary model based least squares algorithm for a dual-rate state space system with time-delay using the data filtering

被引:64
作者
Ding, Feng [1 ]
Liu, Ximei [1 ]
Gu, Ya [1 ]
机构
[1] Qingdao Univ Sci & Technol, Coll Automat & Elect Engn, Qingdao 266042, Peoples R China
来源
JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS | 2016年 / 353卷 / 02期
基金
中国国家自然科学基金;
关键词
NONUNIFORMLY SAMPLED SYSTEMS; PARAMETER-ESTIMATION; STOCHASTIC-SYSTEMS; NONLINEAR-SYSTEMS; IDENTIFICATION; DESIGN;
D O I
10.1016/j.jfranklin.2015.10.025
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
For dual-rate state space systems with time-delay, this paper combines the auxiliary model identification idea with the filtering technique, transforms the state space model into the identification model with different input and output sampling rates, and presents a filtering and auxiliary model based recursive least squares identification algorithm with finite measurement input output data. Compared with the auxiliary model based recursive least squares algorithm, the proposed algorithm can generate more accurate parameter estimates and has a higher computational efficiency because the dimensions of its covariance matrices become small. (C) 2015 The Franklin Institute. Published by Elsevier Ltd. All rights reserved.
引用
收藏
页码:398 / 408
页数:11
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