Hysteretic Damping System Parameter Identification Based on HABC-CS Algorithm

被引:0
|
作者
Kang Weixin [1 ]
Ye Youdao [1 ]
Zhao Tianwei [1 ]
Wagan, Raja Asif [1 ]
机构
[1] Harbin Engn Univ, Dept Informat & Commun Engn, Harbin 150001, Peoples R China
关键词
parameter identification; chaotic searching; bacterial foraging algorithm; adaptive probability; Runge-Kutta algorithm; PARTICLE SWARM OPTIMIZATION;
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Least squares estimate method in parameter identification of hysteretic damping system on the application of ubiquitous computing efficiency is not high, or complicated calculation, calculation accuracy is not high, there is always the problem such as error or error approximation ability is limited. Similar problem happened when inversion analysis of the defect is done in a component torsion wave propagation model, how to get these related parameters quickly and precisely with a good inversion algorithm is the main work we want to do. In this paper, an intelligent algorithm called HABC - CS algorithm is proposed. By introducing chaos search and bacterial foraging algorithm, adaptive probability of Boltzman, strengthen the ability of bacteria foraging behaviour, to speed up the global convergence of bees, improve the accuracy of solution to solve the existed problems of the least squares estimation method. Through the function test platform, the reliability of the HABC - CS algorithm is verified. And through the viscous damping system as an example, the Runge-Kutta algorithm is used to get the simulation data, and then the proposed algorithm is applied to identifying the parameters of hysteretic damping system. At last, the detailed process of parameter identification and the identification result of parameter identification of hysteretic damping system is given in this article.
引用
收藏
页码:1256 / 1261
页数:6
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