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Yunze Guo,Lijuan Wan,Ling Xu,Feng Ding,Ahmed Alsaedi,Tasawar Hayat 제어·로봇·시스템학회 2019 International Journal of Control, Automation, and Vol.17 No.6
This paper focuses on the parameter estimation problem of multivariate output-error autoregressive moving average (M-OEARMA) systems. By applying the auxiliary model identification idea and the decomposition technique, we derive a two-stage recursive least squares algorithm for estimating the M-OEARMA system. Compared with the auxiliary model based recursive least squares algorithm, the proposed algorithm possesses higher identification accuracy. The simulation results confirm the effectiveness of the proposed algorithm.