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Journal of Optimization
Volume 2018, Article ID 3213484, 21 pages
https://doi.org/10.1155/2018/3213484
Research Article

On Metaheuristics for Solving the Parameter Estimation Problem in Dynamic Systems: A Comparative Study

1Research Center of Mechanical Engineering (CIDEM), School of Engineering, Polytechnic of Porto, 4200-072 Porto, Portugal
2ALGORITMI Research Centre, University of Minho, 4710-057 Braga, Portugal
3Faculty of Engineering, University of Porto, 4200-465 Porto, Portugal
4Centre of Mathematics, University of Minho, 4710-057 Braga, Portugal

Correspondence should be addressed to Gisela C. V. Ramadas; tp.ppi.pesi@vcg

Received 16 July 2017; Revised 11 December 2017; Accepted 31 December 2017; Published 29 January 2018

Academic Editor: Liwei Zhang

Copyright © 2018 Gisela C. V. Ramadas et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

This paper presents an experimental study that aims to compare the practical performance of well-known metaheuristics for solving the parameter estimation problem in a dynamic systems context. The metaheuristics produce good quality approximations to the global solution of a finite small-dimensional nonlinear programming problem that emerges from the application of the sequential numerical direct method to the parameter estimation problem. Using statistical hypotheses testing, significant differences in the performance of the metaheuristics, in terms of the average objective function values and average CPU time, are determined. Furthermore, the best obtained solutions are graphically compared in relative terms by means of the performance profiles. The numerical comparisons with other results in the literature show that the tested metaheuristics are effective in achieving good quality solutions with a reduced computational effort.