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Frequency-weighted Model Reduction Using Firefly Algorithm

Tomohiro Hachino, Koichi Tanigawa, Hitoshi Takata, Seiji Fukushima, and Yasutaka Igarashi
Kagoshima University, Kagoshima, Japan
Abstract—This paper deals with a frequency-weighted model reduction for single-input, single-output systems combining the linear least-squares (LS) method with firefly algorithm (FA). The reduced-order model is determined by minimizing the integral of the magnitude squared of the frequency-weighted transfer function error. The denominator parameters and time delay of the reduced-order model are represented by the positions of the fireflies and searched for by the FA, while the numerator parameters are estimated by the linear LS method for each candidate of the denominator parameters and time delay. All the best parameters and the time delay of the reduced-order model are obtained through the search by the fireflies. Simulation results show that the accuracy of the proposed method is comparable to that of the genetic algorithm (GA)-based model reduction algorithm, with smaller computational burden.

Index Terms—model reduction, frequency-weighting, separable least-squares, firefly algorithm

Cite: Tomohiro Hachino, Koichi Tanigawa, Hitoshi Takata, Seiji Fukushima, and Yasutaka Igarashi, "Frequency-weighted Model Reduction Using Firefly Algorithm," Jounal of Automation and Control Engineering, Vol. 3, No. 3, pp. 222-227, June, 2015. doi: 10.12720/joace.3.3.222-227
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