Identification of BoucWen hysteretic systems using particle swarm optimization
In this paper, two variants of the particle swarm optimization (PSO) algorithm are employed for the identification of BoucWen 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 BoucWen hysteretic system that represents a full scale boltedwelded 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.
identification boucwen pso hysteresis genetic algorithms hybrid methods