Stochastic subspace identification via “LQ decomposition”
نویسندگان
چکیده
A new stochastic subspace identification algorithm is developed with the help of a stochastic realization on a finite interval. First, a finite-interval realization algorithm is rederived via “block-LDL decomposition” for a finite string of complete covariance sequence. Next, a stochastic subspace identification method is derived by adapting the finiteinterval realization algorithm to incomplete covariance matrices defined by a finite time-series data. The proposed subspace identification method always works, and computes a stochastic model from the “block-LQ decomposition” without solving any Riccati equations.
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