Parameter estimation for chaotic systems with a Drift Particle Swarm Optimization method

被引：47
|
作者：
Sun, Jun [1 ]
Zhao, Ji [1 ]
Wu, Xiaojun [1 ]
Fang, Wei [1 ]
Cai, Yujie [2 ]
Xu, Wenbo [1 ]
机构：
[1] Jiangnan Univ, Sch Informat Technol, Wuxi 214122, Jiangsu, Peoples R China
[2] Jiangnan Univ, Sch Biotechnol, Key Lab Ind Biotechnol, Wuxi 214122, Jiangsu, Peoples R China
来源：
PHYSICS LETTERS A | 2010年 / 374卷 / 28期
基金：
中国国家自然科学基金;
关键词：
Chaotic systems; Parameter estimation; Global optimization; Particle Swarm Optimization; Drift motion; IDENTIFICATION;
D O I：
10.1016/j.physleta.2010.04.071
中图分类号：
O4 [物理学];
学科分类号：
0702 ;
摘要：
Inspired by the motion of electrons in metal conductors in an electric field, we propose a variant of Particle Swarm Optimization (PSO), called Drift Particle Swarm Optimization (DPSO) algorithm, and apply it in estimating the unknown parameters of chaotic dynamic systems. The principle and procedure of DPSO are presented, and the algorithm is used to identify Lorenz system and Chen system. The experiment results show that for the given parameter configurations, DPSO can identify the parameters of the systems accurately and effectively, and it may be a promising tool for chaotic system identification as well as other numerical optimization problems in physics. (C) 2010 Elsevier B.V. All rights reserved.
引用
收藏
页码：2816 / 2822
页数：7
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