中文摘要：

研究了使用粒子群优化(PSO)算法进行结构系统识别的方法,该方法的基本思想是将结构系统识别问题描述成一个多峰值非线性非凸的优化问题,通过PSO算法发现系统参数的最优估计。利用该方法在输入输出数据不完备且噪声污染条件下,同时在没有系统质量、刚度等先验信息的情况下对结构系统进行了识别,并与基于遗传算法(GA)的结构系统识别方法进行了比较。数值算例及比较结果表明:PSO方法易于实现且计算时占用资源低,并可以成功地对结构系统进行识别,识别效能十分优越。

英文摘要：

A method for identification of structural systems using particle swarm optimization (PSO) algorithm is presented. The basic idea of the method is that the identification problems are cast as a multimodal nonlinear nonconvex programming problem, and then particle swarm optimization algorithm is used to find the optimal estimation of the parameters. Some results obtained with this algorithm are presented for the identification of structural systems under conditions including limited input/output data, noise p...