Multi-objective differential evolution algorithm for stochastic system identification

Zhou Jin, Akira Mita, Li Rongshuai

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

The last decade has witnessed rapid developments in structural system identification methodologies based on intelligent algorithms, which are formulated as multi-modal optimization problems. However, these deterministic methods more or less ignore uncertainties, such as modeling errors and measurement errors, that are inevitably involved in the system identification problem of civil-engineering structures. A new stochastic structural identification method is proposed that takes into account parametric uncertainties in the parameters of building structures. The proposed method merges the advantages of the multi-objective differential evolution optimization algorithm for the non-domination selection strategy and the probability density evolution method for incorporating parametric uncertainties. The results of simulations on identifying the unknown parameters of a structural system demonstrate the feasibility and effectiveness of the proposed method.

Original languageEnglish
Title of host publicationSensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2013
DOIs
Publication statusPublished - 2013 Jun 12
Event2013 SPIE Conference on Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2013 - San Diego, CA, United States
Duration: 2013 Mar 102013 Mar 14

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume8692
ISSN (Print)0277-786X

Other

Other2013 SPIE Conference on Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2013
CountryUnited States
CitySan Diego, CA
Period13/3/1013/3/14

Keywords

  • Multi-objective optimization
  • Stochastic dynamic system
  • Structural system identification

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering

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  • Cite this

    Jin, Z., Mita, A., & Rongshuai, L. (2013). Multi-objective differential evolution algorithm for stochastic system identification. In Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2013 [86923G] (Proceedings of SPIE - The International Society for Optical Engineering; Vol. 8692). https://doi.org/10.1117/12.2006578