A SUBSPACE FITTING METHOD FOR IDENTIFICATION OF LINEAR STATE-SPACE MODELS

被引：10

作者：

SWINDLEHURST, A

ROY, R

OTTERSTEN, B

KAILATH, T

机构：

[1] ARRAYCOMM INC,SANTA CLARA,CA 95054

[2] ROYAL INST TECHNOL,DEPT SIGNALS SENSORS & SYST,S-10044 STOCKHOLM,SWEDEN

[3] STANFORD UNIV,INFORMAT SYST LAB,STANFORD,CA 94305

来源：

IEEE TRANSACTIONS ON AUTOMATIC CONTROL | 1995年 / 40卷 / 02期

基金：

美国国家科学基金会;

关键词：

Number:; MIP-Y; 1101; 12; Acronym:; NSF; Sponsor: National Science Foundation;

D O I：

10.1109/9.341800

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

A new method is presented for the identification of systems parameterized by linear state-space models. The method relies on the concept of subspace fitting, wherein an input/output data model parameterized by the state matrices is found that best fits, in the least-squares sense, the dominant subspace of the measured data. Some empirical results are included to illustrate the performance advantage of the algorithm compared to standard techniques.

引用

页码：311 / 316

页数：6

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