An introduction to models based on Laguerre, Kautz and other related orthonormal functions - part I: linear and uncertain models

被引：24

作者：

Oliveira, Gustavo H. C. ^{[1
]}

da Rosa, Alex ^{[2
]}

Campello, Ricardo J. G. B. ^{[3
]}

Machado, Jeremias B. ^{[4
]}

Amaral, Wagner C. ^{[5
]}

机构：

[1] Fed Univ Parana UFPR, Dept Elect Engn, BR-80215901 Curitiba, Parana, Brazil

[2] Univ Brasilia UnB, Dept Elect Engn, BR-70910900 Brasilia, DF, Brazil

[3] Univ Sao Paulo, Dept Comp Sci, BR-13560970 Sao Carlos, SP, Brazil

[4] Fed Univ Itajuba UNIFEI, Engn & Informat Technol Inst, BR-37500903 Itajuba, MG, Brazil

[5] Univ Estadual Campinas, UNICAMP, Sch Elect & Comp Engn, BR-13083852 Campinas, SP, Brazil

来源：

INTERNATIONAL JOURNAL OF MODELLING IDENTIFICATION AND CONTROL | 2011年 / 14卷 / 1-2期

基金：

巴西圣保罗研究基金会;

关键词：

modelling; system identification; robust identification; orthonormal basis functions; OBF; linear systems;

D O I：

10.1504/IJMIC.2011.042346

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 provides an overview of system identification using orthonormal basis function models, such as those based on Laguerre, Kautz, and generalised orthonormal basis functions. The paper is separated in two parts. In this first part, the mathematical foundations of these models as well as their advantages and limitations are discussed within the context of linear and robust system identification. The second part approaches the issues related with non-linear models. The discussions comprise a broad bibliographical survey of the subjects involving linear models within the orthonormal basis functions framework. Theoretical and practical issues regarding the identification of these models are presented and illustrated by means of a case study involving a polymerisation process.

引用

页码：121 / 132

页数：12

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