2012
DOI: 10.2478/v10171-012-0013-3
|View full text |Cite
|
Sign up to set email alerts
|

Application of a PSO algorithm for identification of the parameters of Jiles-Atherton hysteresis model

Abstract: Abstract:In the paper an algorithm and computer code for the identification of the hysteresis parameters of the Jiles-Atherton model have been presented. For the identification the particle swarm optimization method (PSO) has been applied. In the optimization procedure five design variables has been assumed. The computer code has been elaborated using Delphi environment. Three types of material have been examined. The results of optimization have been compared to experimental ones. Selected results of the calc… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
1
1
1

Citation Types

0
10
0

Year Published

2013
2013
2017
2017

Publication Types

Select...
6

Relationship

3
3

Authors

Journals

citations
Cited by 16 publications
(10 citation statements)
references
References 19 publications
0
10
0
Order By: Relevance
“…To determine the number of particles in the swarm and values of PSO factors (w 1 , c 1 , c 2 ) authors utilized their experience gained in the solution of other optimization tasks using PSO algorithm (Knypiński et al, 2009(Knypiński et al, , 2012. The calculations have been performed dozen times for different starting population.…”
Section: Resultsmentioning
confidence: 99%
See 1 more Smart Citation
“…To determine the number of particles in the swarm and values of PSO factors (w 1 , c 1 , c 2 ) authors utilized their experience gained in the solution of other optimization tasks using PSO algorithm (Knypiński et al, 2009(Knypiński et al, , 2012. The calculations have been performed dozen times for different starting population.…”
Section: Resultsmentioning
confidence: 99%
“…These variables form the design variable vector z ¼ [l m g m r m z s ] T . In the studied algorithm the variables z have been transformed into dimensionless quantities s according to the formula (Knypiński et al, 2012):…”
Section: Startmentioning
confidence: 99%
“…After a number of iterations the optimal solution, indicated by swarming candidates, is determined. PSO has been applied for estimation of JA model parameters by Marion et al [28] and Knypiński et al [29].…”
Section: Comparison Of Different Estimation Techniquesmentioning
confidence: 99%
“…It was reported in Jędryczka et al (2009) that the J-M model has been successfully utilized to simulate of coupled electromagnetic, fluid dynamic, and motion phenomena. This model can be used in FEM calculations (Gyselinck et al, 2004) and recently, an algorithm and computer code was presented (Knypiński et al, 2012) to effectively determine several parameters of the J-A model.…”
Section: Introductionmentioning
confidence: 99%