Title :
GATEUR model updating based on QGA-PSO algorithm
Author :
Yuling, Qin ; Xianren, Kong ; Wenbo, Luo
Abstract :
In this paper the quadratic search-based Genetic-Particle Swarm Optimization Algorithm (QGA-PSO) with storage and comparison vector was proposed, which largely improved the efficiency and precision of Genetic-Particle Swarm Optimization Algorithm (GA-PSO). The finite element model (FEM) of the GARTEUR benchmark was updated using QGA-PSO as well as GA-PSO, the updated model can both reproduce the modal properties in the test range and predict the properties out of the test range as well as the modal properties of the structure with modified parameters, which proves the validity of the QGA-PSO model updating method.
Keywords :
finite element analysis; genetic algorithms; particle swarm optimisation; search problems; vectors; GARTEUR model; comparison vector; finite element model; group for aeronautical research and technology in Europe; quadratic search-based genetic-particle swarm optimization algorithm; Algorithm design and analysis; Analytical models; Atmospheric modeling; Data models; Finite element methods; Mathematical model; Predictive models;
Conference_Titel :
Systems and Control in Aeronautics and Astronautics (ISSCAA), 2010 3rd International Symposium on
Conference_Location :
Harbin
Print_ISBN :
978-1-4244-6043-4
Electronic_ISBN :
978-1-4244-7505-6
DOI :
10.1109/ISSCAA.2010.5632259