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CBA2018-0556 Modelagem e Identificação de Sistemas

An Improved Symbiotic Organisms Search Algorithm Applied to Nonlinear System Parameter Estimation Problems

Fernando Lucas Moura1; Leonardo Ramos Rodrigues2; Takashi Yoneyama1

1 Instituto Tecnológico de Aeronáutica; 2 Instituto de Aeronáutica e Espaço

Baixar PDF doi:10.20906/CPS/CBA2018-0556

Resumo

In this paper, we propose a modified 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 simplifies 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.

Palavras-chave: Algoritmo de Busca por Organismos Simbióticos; Identificação de Parâmetros; Sistemas Não Lineares

Como citar

Fernando Lucas Moura; Leonardo Ramos Rodrigues; Takashi Yoneyama. “An Improved Symbiotic Organisms Search Algorithm Applied to Nonlinear System Parameter Estimation Problems”. XXII Congresso Brasileiro de Automática. CBA2018. 2018. DOI: 10.20906/CPS/CBA2018-0556