Particle Swarm Optimization for Chaotic System Parameter Estimation

被引：3
|
作者：
Samanta, B. [1 ]
Nataraj, C. [1 ]
机构：
[1] Villanova Univ, Dept Mech Engn, Villanova, PA 19085 USA
来源：
2009 IEEE SWARM INTELLIGENCE SYMPOSIUM | 2009年
关键词：
SYNCHRONIZATION; CONVERGENCE; STATE;
D O I：
10.1109/SIS.2009.4937847
中图分类号：
TP301 [理论、方法];
学科分类号：
081202 ;
摘要：
A study is presented on the application of particle swarm optimization (PSO) for estimation of parameters in chaotic systems. The parameter estimation is formulated as a nonlinear optimization problem using PSO to minimize the synchronization error for the observable states of the actual system and its mathematical model. The procedure is illustrated using a typical chaotic system of Lorenz equations. The effectiveness of different variants of PSO on parameter estimation is studied with a wide search range of parameters. The results show the capability of the proposed PSO based approach in estimating the chaotic system parameters even in the presence of observation noise.
引用
收藏
页码：74 / 80
页数：7
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