Recursive Subspace Model Identification Based On Vector Autoregressive Modelling

نویسندگان

  • Ping Wu
  • ChunJie Yang
  • ZhiHuan Song
چکیده

Recursive subspace model identification (RSMI) has been developed for a decade. Most of RSMIs are only applied for open loop data. In this paper, we propose a new recursive subspace model identification which can be applied under open loop and closed loop data. The key technique of this derivation of the proposed algorithm is to bring the Vector Auto Regressive with eXogenous input (VARX) models into RSMI. Numerical studies on a closed loop identification problem show the effectiveness of the proposed algorithm.

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تاریخ انتشار 2008