Artículos de revistas
An Introduction To Models Based On Laguerre, Kautz And Other Related Orthonormal Functions - Part I: Linear And Uncertain Models
Registro en:
International Journal Of Modelling, Identification And Control. , v. 14, n. 01/02/15, p. 121 - 132, 2011.
17466172
10.1504/IJMIC.2011.042346
2-s2.0-80052474163
Autor
Oliveira G.H.C.
Da Rosa A.
Campello R.J.G.B.
Machado J.B.
Amaral W.C.
Institución
Resumen
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. Copyright © 2011 Inderscience Enterprises Ltd. 14 01/02/15 121 132 Aguirre, L.A., Correa, M.V., Cassini, C., Nonlinearities in NARX polynomial models: Representation and estimation (2002) IEE Proc. 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