Set-membership algorithm for identification of structural parameters based on ARMA time-series model

Identification of structural parameters by using observation data with noise in time domain was studied. Autoregressive moving-average (ARMA) model of a vibrating structure was established, and the identification problem of structural parameters was transformed into the identification problem of parameters of ARMA model. Based on the assumption of the unknown-but-bounded (UBB) noise, an interval algorithm for set-membership identification of parameters of linear time-invariant system was used to seek the minimal hyper-rectangle (or interval vector) of parameters, which is compatible with the measurements and the bounded noise, so that the structural parameters can be obtained. The numerical example illustrates its feasibility and effectiveness in comparison with the least squares algorithm.