Open Access
Translator Disclaimer
2014 A Comparison of Evolutionary Computation Techniques for IIR Model Identification
Erik Cuevas, Jorge Gálvez, Salvador Hinojosa, Omar Avalos, Daniel Zaldívar, Marco Pérez-Cisneros
J. Appl. Math. 2014: 1-9 (2014). DOI: 10.1155/2014/827206

Abstract

System identification is a complex optimization problem which has recently attracted the attention in the field of science and engineering. In particular, the use of infinite impulse response (IIR) models for identification is preferred over their equivalent FIR (finite impulse response) models since the former yield more accurate models of physical plants for real world applications. However, IIR structures tend to produce multimodal error surfaces whose cost functions are significantly difficult to minimize. Evolutionary computation techniques (ECT) are used to estimate the solution to complex optimization problems. They are often designed to meet the requirements of particular problems because no single optimization algorithm can solve all problems competitively. Therefore, when new algorithms are proposed, their relative efficacies must be appropriately evaluated. Several comparisons among ECT have been reported in the literature. Nevertheless, they suffer from one limitation: their conclusions are based on the performance of popular evolutionary approaches over a set of synthetic functions with exact solutions and well-known behaviors, without considering the application context or including recent developments. This study presents the comparison of various evolutionary computation optimization techniques applied to IIR model identification. Results over several models are presented and statistically validated.

Citation

Download Citation

Erik Cuevas. Jorge Gálvez. Salvador Hinojosa. Omar Avalos. Daniel Zaldívar. Marco Pérez-Cisneros. "A Comparison of Evolutionary Computation Techniques for IIR Model Identification." J. Appl. Math. 2014 1 - 9, 2014. https://doi.org/10.1155/2014/827206

Information

Published: 2014
First available in Project Euclid: 2 March 2015

zbMATH: 07131902
Digital Object Identifier: 10.1155/2014/827206

Rights: Copyright © 2014 Hindawi

JOURNAL ARTICLE
9 PAGES


SHARE
Vol.2014 • 2014
Back to Top