Identification of Bouc-Wen hysteretic systems using particle swarm optimization
In this paper, two variants of the particle swarm optimization (PSO) algorithm are employed for the identification of Bouc-Wen hysteretic systems. The first variant is simple while the other is enhanced, as it implements additional operators. The algorithms are utilized for the identification of a Bouc-Wen hysteretic system that represents a full scale bolted-welded steel connection. The purpose of this work is to assess their comparative performance against other evolutionary algorithms in a highly non-linear identification problem on various levels of computational budget. The enhanced PSO algorithm outperforms its competitors in terms of both accuracy and robustness. (C) 2010 Elsevier Ltd. All rights reserved.
identification bouc-wen pso hysteresis genetic algorithms hybrid methods