Creating Sparse Rational Approximations for Linear Fractional Representations Using Genetic Programming

Created by W.Langdon from gp-bibliography.bib Revision:1.8051

@InProceedings{conf/iconas/HardierRS13,

• author = "Georges Hardier and Clement Roos and Cedric Seren",
• title = "Creating Sparse Rational Approximations for Linear Fractional Representations Using Genetic Programming",
• booktitle = "3rd IFAC International Conference on Intelligent Control and Automation Science, ICONS 2013",
• year = "2013",
• editor = "Pedro M. Ferreira",
• pages = "393--398",
• address = "Sichuan, Chengdu, China",
• month = sep # " 2-4",
• publisher = "International Federation of Automatic Control",
• keywords = "genetic algorithms, genetic programming, rational approximation, Linear Fractional Representation, mu-analysis",
• bibdate = "2014-11-28",
• bibsource = "DBLP, http://dblp.uni-trier.de/db/conf/iconas/iconas2013.html#HardierRS13",
• isbn13 = "978-3-902823-45-8",
• broken = "http://www.ifac-papersonline.net/Detailed/63487.html",
• DOI = "doi:10.3182/20130902-3-CN-3020.00065",
• URL = "https://w3.onera.fr/smac/tracker",
• size = "6 pages",
• abstract = "The objective of this paper is to stress that the size of a Linear Fractional Representation (LFR) significantly depends on the way tabulated or irrational data are approximated during the modelling process. It is notably shown that rational approximants can result in much smaller LFR than polynomial ones. In this context, a new method is introduced to generate sparse rational models, which avoid data overfitting and lead to simple yet accurate LFR, thanks to a symbolic regression technique. Genetic Programming is implemented to select sparse monomials and coupled with a nonlinear iterative procedure to estimate the coefficients of the surrogate model. Furthermore, a mu-analysis based proof is given to check the nonsingularity of the resulting rational functions. The proposed method is evaluated on an aeronautical example and successfully compared to more classical approaches.",
• notes = "Systems Control and Flight Dynamics Department, ONERA The French Aerospace Lab,Toulouse, France.

  https://tc.ifac-control.org/3/2/activities/newsletter-05-ifac-tc-1-3-discrete-event-and-hybrid-system-january-2007 http: www.ifac-papersonline.net Intelligent_Control_and_Automation_Science 3rd_IFAC_International_Conference_on_Intelligent_Control_and_Automation_Science__2013_ index.htm

  See also https://hal.archives-ouvertes.fr/hal-01088602/document",

}

Genetic Programming entries for Georges Hardier Clement Roos Cedric Seren

Citations