TY - GEN
T1 - Multi-objective differential evolution algorithm for stochastic system identification
AU - Jin, Zhou
AU - Mita, Akira
AU - Rongshuai, Li
PY - 2013/6/12
Y1 - 2013/6/12
N2 - 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.
AB - 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.
KW - Multi-objective optimization
KW - Stochastic dynamic system
KW - Structural system identification
UR - http://www.scopus.com/inward/record.url?scp=84878721825&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84878721825&partnerID=8YFLogxK
U2 - 10.1117/12.2006578
DO - 10.1117/12.2006578
M3 - Conference contribution
AN - SCOPUS:84878721825
SN - 9780819494757
T3 - Proceedings of SPIE - The International Society for Optical Engineering
BT - Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2013
T2 - 2013 SPIE Conference on Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2013
Y2 - 10 March 2013 through 14 March 2013
ER -