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 ||·|| ∞ and ||·||1 norms have been considered simultaneously, is presented to illustrate the technique.
Partially supported by MEC (Spanish government) and FEDER funds: projects DPI2005-07835, DPI2004-8383-C03-02 and GVA-026.
This is a preview of subscription content, log in via an institution to check access.
Preview
Unable to display preview. Download preview PDF.
We’re sorry, something doesn't seem to be working properly.
Please try refreshing the page. If that doesn't work, please contact support so we can address the problem.
References
Belforte, G., Bona, B., Cerone, V.: Parameter estimation algoritms for a set-membership description of uncertainty. Automatica 26(5), 887–898 (1990)
Chisci, L., Garulli, A., Vicino, A., Zappa, G.: Block recursive parallelotopic bounding in set membership identification. Automatica 34(1), 15–22 (1988)
Fogel, E., Huang, F.: On the value of information in system identification-bounded noise case. Automatica 12(12), 229–238 (1982)
Herrero, J.M.: Non-linear robust identification using evolutionary algorithms. PhD. Thesis. Polytechnic University of Valencia, Spain (2006)
Keesman, K.J., Stappers, R.: Nonlinear set-membership estimation: A support vector machine approach. J. Inv. Ill-Posed Problems 12(1), 27–41 (2004)
Ljung, L.: System identification, theory for the user, 2nd edn. Prentice-Hall, Englewood Cliffs (1999)
Reinelt, W., Garulli, A., Ljung, L.: Comparing different approaches to model error modelling in robust identification. Automatica 38(5), 787–803 (2002)
Walter, E., Piet-Lahanier, H.: Estimation of parameter bounds from bounded-error data: A survey. Mathematics and computers in Simulation 32, 449–468 (1990)
Walter, E., Kieffer, M.: Interval analysis for guaranteed nonlinear parameter estimation. In: Proc. of the 13th IFAC Symposium on System Identification (2003)
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 2007 Springer Berlin Heidelberg
About this paper
Cite this paper
Herrero, J.M., Blasco, X., Martínez, M., Salcedo, J.V. (2007). Non-linear Robust Identification: Application to a Thermal Process. In: Mira, J., Álvarez, J.R. (eds) Bio-inspired Modeling of Cognitive Tasks. IWINAC 2007. Lecture Notes in Computer Science, vol 4527. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-73053-8_46
Download citation
DOI: https://doi.org/10.1007/978-3-540-73053-8_46
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-73052-1
Online ISBN: 978-3-540-73053-8
eBook Packages: Computer ScienceComputer Science (R0)