Parametric identification of bouc-wen hysteresis model for piezoelectric ceramic actuator based on immune particle swarm optimization algorithm

Ning Dong, Hong Juan Li, Xiang Dong Liu, Chun Xia Cai

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Citation (Scopus)

Abstract

This paper is concerned with the parametric identification based on immune particle swarm optimization (IPSO) algorithm for Bouc-Wen model of piezoelectric ceramic actuators (PCA). IPSO algorithm is an algorithm that introduces the immunological memory and selection mechanism of concentration of antibody of immune system to PSO algorithm. It is used to identify unknown parameters of Bouc-Wen model, one of the most widely used parametric models of hysteresis in mechanics. The experimental results reveal that IPSO algorithm has better precision and convergence.

Original languageEnglish
Title of host publicationMicro-Nano Technology XIV
PublisherTrans Tech Publications Ltd.
Pages509-515
Number of pages7
ISBN (Print)9783037857397
DOIs
Publication statusPublished - 2013
Event14th Annual Conference and the 3rd International Conference of the Chinese Society of Micro-Nano Technology, CSMNT 2012 - Hangzhou, China
Duration: 4 Nov 20127 Nov 2012

Publication series

NameKey Engineering Materials
Volume562-565
ISSN (Print)1013-9826
ISSN (Electronic)1662-9795

Conference

Conference14th Annual Conference and the 3rd International Conference of the Chinese Society of Micro-Nano Technology, CSMNT 2012
Country/TerritoryChina
CityHangzhou
Period4/11/127/11/12

Keywords

  • Bouc-wen
  • Identification
  • Immune particle swarm optimization
  • Piezoelectric ceramic actuator

Fingerprint

Dive into the research topics of 'Parametric identification of bouc-wen hysteresis model for piezoelectric ceramic actuator based on immune particle swarm optimization algorithm'. Together they form a unique fingerprint.

Cite this