Parameter identification of dynamical systems based on improved particle swarm optimization

被引：0
|
作者：
Ye, Meiying [1 ]
机构：
[1] Zhejiang Normal Univ, Coll Math & Phys, Jinhua 321004, Peoples R China
来源：
INTELLIGENT CONTROL AND AUTOMATION | 2006年 / 344卷
关键词：
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：
Improved Particle Swarm Optimization (IPSO), which is a new robust stochastic evolutionary computation algorithm based on the movement and intelligence of swarms, is proposed to estimate parameters of nonlinear dynamical systems. The effectiveness of the IPSO algorithms is compared with Genetic Algorithms (GAs) and standard Particle Swarm Optimization (PSO). Simulation results of two kinds of nonlinear dynamical systems will be illustrated to show that the more accurate estimations can be achieved by using the IPSO method.
引用
收藏
页码：351 / 360
页数：10
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