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
相关论文
共 50 条
  • [31] Parameter estimation for fractional-order chaotic systems by improved bird swarm optimization algorithm
    Zhang, Pei
    Yang, Renyu
    Yang, Renhuan
    Ren, Gong
    Yang, Xiuzeng
    Xu, Chuangbiao
    Xu, Baoguo
    Zhang, Huatao
    Cai, Yanning
    Lu, Yaosheng
    INTERNATIONAL JOURNAL OF MODERN PHYSICS C, 2019, 30 (11):
  • [32] A Particle Swarm Optimization Approach for Parameter Identification of Lorenz Chaotic System
    Modarres, Hamidreza
    Alfi, Alireza
    IECON: 2009 35TH ANNUAL CONFERENCE OF IEEE INDUSTRIAL ELECTRONICS, VOLS 1-6, 2009, : 3127 - +
  • [33] Distributed and robust parameter estimation of IIR systems using incremental particle swarm optimization
    Majhi, Babita
    Panda, Ganapati
    DIGITAL SIGNAL PROCESSING, 2013, 23 (04) : 1303 - 1313
  • [34] A Comparison of Genetic Algorithms and Particle Swarm Optimization for Parameter Estimation in Stochastic Biochemical Systems
    Besozzi, D.
    Cazzaniga, P.
    Mauri, G.
    Pescini, D.
    Vanneschi, L.
    EVOLUTIONARY COMPUTATION, MACHINE LEARNING AND DATA MINING IN BIOINFORMATICS, PROCEEDINGS, 2009, 5483 : 116 - +
  • [35] Particle Swarm Optimization-Based Gyro Drift Estimation Method for Inertial Navigation System
    He, Hongyang
    Zhu, Bing
    Zha, Feng
    IEEE ACCESS, 2019, 7 : 55788 - 55796
  • [36] Research on particle swarm optimization algorithm with characteristic of quantum parallel and its application in parameter estimation for fractional-order chaotic systems
    Huang Yu
    Liu Yu-Feng
    Peng Zhi-Min
    Ding Yan-Jun
    ACTA PHYSICA SINICA, 2015, 64 (03)
  • [37] Parameter Estimation of Bioprocesses via Parallel Particle Swarm Optimization
    Sendrescu, Dorin
    Petre, Emil
    Bobasu, Eugen
    Roman, Monica
    2016 20TH INTERNATIONAL CONFERENCE ON SYSTEM THEORY, CONTROL AND COMPUTING (ICSTCC), 2016, : 336 - 341
  • [38] PARAMETER ESTIMATION TO AN ANEMIA MODEL USING THE PARTICLE SWARM OPTIMIZATION
    Ahmad, Arshed A.
    Sari, Murat
    SIGMA JOURNAL OF ENGINEERING AND NATURAL SCIENCES-SIGMA MUHENDISLIK VE FEN BILIMLERI DERGISI, 2019, 37 (04): : 1331 - 1343
  • [39] Parameter Estimation for Asymptotic Regression Model by Particle Swarm Optimization
    Xu, Xing
    Li, Yuanxiang
    Wu, Yu
    Du, Xin
    WORLD SUMMIT ON GENETIC AND EVOLUTIONARY COMPUTATION (GEC 09), 2009, : 679 - 686
  • [40] Application of particle swarm optimization to the estimation of the TSInSAR deformation parameter
    Xue, Feiyang
    Lv, Xiaolei
    Chai, Huiming
    Huang, Huibao
    REMOTE SENSING LETTERS, 2019, 10 (08) : 756 - 765
12345