Frequency domain identification of ARX models in the presence of additive input-output noise

被引：1

作者：

Soverini, Umberto ^{[1
]}

Soderstrom, Torsten ^{[2
]}

机构：

[1] Univ Bologna, Dept Elect Elect & Informat Engn, Bologna, Italy

[2] Uppsala Univ, Dept Informat Technol, Uppsala, Sweden

来源：

IFAC PAPERSONLINE | 2017年 / 50卷 / 01期

关键词：

System identification; ARX models; Frisch Scheme; Discrete Fourier Transform; LEAST-SQUARES; FRISCH SCHEME;

D O I：

10.1016/j.ifacol.2017.08.1023

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 describes a new approach for identifying ARX models from a finite number of measurements, in presence of additive and uncorrelated white noise. The proposed algorithm is based on some theoretical results concerning the so-called dynamic Frisch Scheme. As a major novelty, the proposed approach deals with frequency domain data. In some aspects, the method resembles the characteristics of other identification algorithms, originally developed in the time domain. The proposed method is compared with other techniques by means of Monte Carlo simulations. The benefits of filtering the data and using only part of the frequency domain is highlighted by means of a numerical example. (C) 2017, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.

引用

页码：6226 / 6231

页数：6

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