Identification methods for transfer function estimation using dual-rate sampled data

In order to get the unbiased parameter estimation of the transfer function from dual-rate sampled data. This paper studies dual-rate system identification using model equivalent method and presents an auxiliary model based method. The basic idea is to replace the output data of the system by the output of an auxiliary model, and the recursive least squares parameter estimation revised by the errors between the system output and auxiliary model output. Finally, the advantages of the proposed approach are shown by simulation tests.