Parameter estimation for chaotic system based on particle swarm optimization

被引：45
|
作者：
Gao, F [1 ]
Tong, HQ [1 ]
机构：
[1] Wuhan Univ Technol, Sch Sci, Wuhan 430070, Peoples R China
来源：
ACTA PHYSICA SINICA | 2006年 / 55卷 / 02期
关键词：
chaos system; parameter estimation; on-line estimation; particle swarm optimization;
D O I：
10.7498/aps.55.577
中图分类号：
O4 [物理学];
学科分类号：
0702 ;
摘要：
It's of vital importance to estimate the unknown parameters of chaos systems in chaos control and synchronization. We firstly improve the newly developed particle swarm optimization (PSO) in view of the population initialization and objective function treatment. Then we use the improved algorithms for parameter estimation and on-line estimation of chaotic system for its global searching ability. Experiments show that the improved method has better adaptability, reliability and high precision is robust to noise. It is proved to be a successful approach in parameter estimation for chaotic systems.
引用
收藏
页码：577 / 582
页数：6
相关论文
共 16 条
  • [1] Chen G., 2003, DYNAMICS LORENZ SYST
  • [2] An approach of parameter estimation for a chaotic system based on genetic algorithm
    Dai, D
    Ma, XK
    Li, FC
    You, Y
    [J]. ACTA PHYSICA SINICA, 2002, 51 (11) : 2459 - 2462
  • [3] Duchâteau A, 1999, INT J CONTROL, V72, P727, DOI 10.1080/002071799220894
  • [4] Eberhart RC, 2000, IEEE C EVOL COMPUTAT, P84, DOI 10.1109/CEC.2000.870279
  • [5] FANG J, 2002, CONTROL CHAOS DEV HI, P32108
  • [6] Parameters identification and control of Lorenz chaotic system
    Guan, XP
    Peng, HP
    Li, LX
    Wang, YQ
    [J]. ACTA PHYSICA SINICA, 2001, 50 (01) : 26 - 29
  • [7] MA CX, 1999, UNIFORM DESIGN BASED, P32108
  • [8] On the alleviation of the problem of local minima in back-propagation
    Magoulas, GD
    Vrahatis, MN
    Androulakis, GS
    [J]. NONLINEAR ANALYSIS-THEORY METHODS & APPLICATIONS, 1997, 30 (07) : 4545 - 4550
  • [9] MICHALEWICZ Z, 2000, SOLVE MODERN HEURIST
  • [10] Recent approaches to global optimization problems through Particle Swarm Optimization
    K.E. Parsopoulos
    M.N. Vrahatis
    [J]. Natural Computing, 2002, 1 (2-3) : 235 - 306
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