Article ID: | iaor20112747 |
Volume: | 53 |
Issue: | 9-10 |
Start Page Number: | 1664 |
End Page Number: | 1669 |
Publication Date: | May 2011 |
Journal: | Mathematical and Computer Modelling |
Authors: | Ding Ruifeng, Bao Bo, Xu Yingqin, Sheng Jie |
Keywords: | ARIMA processes |
Difficulties of identification for multivariable controlled autoregressive moving average (ARMA) systems lie in that there exist unknown noise terms in the information vector, and the iterative identification can be used for the system with unknown terms in the information vector. By means of the hierarchical identification principle, those noise terms in the information vector are replaced with the estimated residuals and a least squares based iterative algorithm is proposed for multivariable controlled ARMA systems. The simulation results indicate that the proposed algorithm is effective.