计算力学学报2017，Vol.34Issue(1)：106-110,5.DOI:10.7511/jslx201701015
基于改进萤火虫算法的移动车辆参数识别
Identification of moving vehicular parameters based on Improved Glowworm Swarm Optimization algorithm
摘要
Abstract
This paper presents an indirect method for the identification of parameters of moving vehicles based on Glowworm Swarm Optimization (GSO) algorithm.Each moving vehicle is modelled as a four-degree-of-freedom system with twelve parameters.The equation of the bridge-vehicle system is established by finite element method.And Newmark direct integration method is used to calculate the dynamic response of the system.A local search method and eliminated system at last one are brought in the movement phase of GSO to enhance the accuracy and convergence rate of the algorithm.Acceleration measurements at selected stations on the vehicle are used to identify the parameters of the moving vehicle with the IGSO algorithm.Several test cases are studied to verify the efficiency of the method and the results show that the proposed method is not sensitive to measurement noise.关键词
萤火虫优化算法/车桥耦合系统/移动车辆/加速度响应/参数识别Key words
Glowworm Swarm Optimization algorithm/bridge-vehicle system/moving vehicle/acceleration response/parameter identification分类
数理科学引用本文复制引用
李海龙,吕中荣,刘济科..基于改进萤火虫算法的移动车辆参数识别[J].计算力学学报,2017,34(1):106-110,5.基金项目
国家自然科学基金(11172333,11272361)资助项目. （11172333,11272361）
