Recursive least squares identification for multirate multi-input single-output systems

被引：3
|
作者：
Han, Lili [1 ,2 ]
Sheng, Jie [3 ]
Ding, Feng [2 ]
Shi, Yang [4 ]
机构：
[1] Univ Saskatchewan, Saskatoon, SK, Canada
[2] Jiangnan Univ, Control Sci & Engn Res Ctr, Wuxi 214122, Peoples R China
[3] Washington Univ, Inst Technol, Tacoma, WA 98402 USA
[4] Univ Saskatchewan, Dept Engn Mech, Saskatoon, SK S7N 5A9, Canada
来源：
2009 AMERICAN CONTROL CONFERENCE, VOLS 1-9 | 2009年
基金：
加拿大自然科学与工程研究理事会;
关键词：
SAMPLED-DATA SYSTEMS; DUAL-RATE SYSTEMS; RATE STOCHASTIC-SYSTEMS; FAST-RATE MODELS; PARAMETER-ESTIMATION; AUXILIARY MODEL; DESIGN; STATE;
D O I：
10.1109/ACC.2009.5160447
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
This paper derives state-space models for multirate multi-input sampled-data systems. Based on the corresponding transfer function models, an auxiliary model based recursive least squares algorithm is presented to identify the model parameters of the multirate systems from the multirate input-output data. Further, convergence properties of the proposed algorithm are analyzed. An illustrative example is given.
引用
收藏
页码：5604 / +
页数：2
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