作者: Zhu, Yucai; Hjalmarsson, Hakan
来源：AUTOMATICA 卷: 65 页: 170-182 出版年: MAR 2016
An algorithm for identification of single-input single-output Box–Jenkins models is presented. firstly a high order ARX model is estimated; secondly, the input–output data is filtered with the inverse of the estimated disturbance model; thirdly, the filtered data is used in the Steiglitz-McBride method to recover the system dynamics; finally, the noise model is recovered by estimating an ARMA model from the residuals of the third step. A Monte Carlo simulation study with an oscillatory system is presented and these results are complemented with an industrial case study.