Identification of hysteretic systems: PSO

In this project, 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 source of xlOptimizer has been used for the identification purposes. The Enhanced PSO algorithm outperforms its competitors in terms of both accuracy and robustness. 

For more information, please refer to the following paper:

Charalampakis, A. E., Dimou, C. K., "Identification of Bouc–Wen Hysteretic Systems using Particle Swarm Optimization", Computers and Structures, 88 (2010): 1197–1205,