AN IMPROVED SYMBIOTIC ORGANISMS SEARCH ALGORITHM APPLIED TO NONLINEAR SYSTEM PARAMETER ESTIMATION PROBLEMS

FERNANDO LUCAS MOURA; LEONARDO   RAMOS RODRIGUES; TAKASHI YONEYAMA

doi:10.20906/CBA2022/378

FERNANDO LUCAS MOURA
LEONARDO RAMOS RODRIGUES Instituto de Aeronáutica e Espaço
TAKASHI YONEYAMA Instituto Tecnológico de Aeronáutica

DOI: https://doi.org/10.20906/CBA2022/378

Keywords: Symbiotic organisms search algorithm, Parameter identification, Nonlinear systems

Abstract

In this paper, we propose a modied version of the Symbiotic Organisms Search (SOS) algorithm.
The proposed version of SOS is applied to the nonlinear system parameter estimation problem. Numerical
experiments are carried out to evaluate the performance of the proposed algorithm using two nonlinear models: the Output Error Polynomial (OEP) and the Output Error Rational (OER) models. The results show that the proposed algorithm provided good accuracy in both models, outperforming other algorithms. Also, the reduced number of parameters to be chosen simplies the parameter tuning process of SOS when compared with other metaheuristics. Based on the results, the proposed version of SOS can be considered as a good alternative to solve nonlinear system parameter estimation problems.