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

Gustavo H.C. Oliveira*, Alex Da Rosa, Ricardo J.G.B. Campello, Jeremias B. Machado, Wagner C. Amaral

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Abstract

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.

OriginalsprogEngelsk
TidsskriftInternational Journal of Modelling, Identification and Control
Vol/bind14
Udgave nummer1-2
Sider (fra-til)121-132
ISSN1746-6172
DOI
StatusUdgivet - sep. 2011
Udgivet eksterntJa

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