Least Squares Based Iterative Identification Algorithm for Output Error Autoregressive Systems Using the Decomposition Technique and the Data Filtering

摘要

This paper derives a least squares based iterative identification algorithm for output error autoregressive systems using the decomposition technique and the data filtering. The basic idea is to use the data filtering technique to transform the original identification model into an output error model, to decompose this model into two subsystems and to identify each subsystem, respectively. Compared with the least squares based iterative algorithm, the proposed algorithm has a less computational burden. The simulation results verify the theoretical finding.