Abstract
This paper considers the identification problem of non-uniformly sampled-data (NUSD) systems with asynchronous input and output data. By using the lifting technique, the lifted transfer function (L-TF) model of the asynchronous NUSD systems is derived. Furthermore, an auxiliary model based recursive least squares (AM-RLS) algorithm is developed to directly identify the L-TF model. In order to avoid the causality constraint problem and improve the computational efficiency, a coupled AM-RLS algorithm is proposed to identify the subsystems of the L-TF model. The effectiveness of the proposed identification algorithms is validated by two simulation examples.
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