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Non-linear Robust Identification: Application to a Thermal Process.

Authors :
Hutchison, David
Kanade, Takeo
Kittler, Josef
Kleinberg, Jon M.
Mattern, Friedemann
Mitchell, John C.
Naor, Moni
Nierstrasz, Oscar
Rangan, C. Pandu
Steffen, Bernhard
Sudan, Madhu
Terzopoulos, Demetri
Tygar, Doug
Vardi, Moshe Y.
Weikum, Gerhard
Mira, José
Álvarez, José R.
Herrero, J. M.
Blasco, X.
Martínez, M.
Source :
Bio-inspired Modeling of Cognitive Tasks; 2007, p457-466, 10p
Publication Year :
2007

Abstract

In this article, a methodology to obtain the Feasible Parameter Set (FPS) and a nominal model in a non-linear robust identification problem is presented. Several norms are taken into account simultaneously to define the FPS which improves the model quality but, as counterpart, it increases the optimization problem complexity. To determine the FPS a multimodal optimization problem with an infinite number of minima, which constitute the FPS, is presented and a special evolutionary algorithm (ε−GA) is used to characterize it. Finally, an application to a thermal process identification, where <INNOPIPE><INNOPIPE>·<INNOPIPE><INNOPIPE> ∞  and <INNOPIPE><INNOPIPE>·<INNOPIPE><INNOPIPE>1 norms have been considered simultaneously, is presented to illustrate the technique. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISBNs :
9783540730521
Database :
Supplemental Index
Journal :
Bio-inspired Modeling of Cognitive Tasks
Publication Type :
Book
Accession number :
33214140
Full Text :
https://doi.org/10.1007/978-3-540-73053-8_46