부산대학교 도서관

In this paper, an alternative consistent subspace identification method using parity space is proposed. The future/past input data and the past output data are used to construct the instrument variable to eliminate thenoise effect on consistent estimation. The extended observability matrix and the triangular block-Toeplitz matrixare then retrieved from a parity space of the noise-free matrix using a singular value decomposition based method. The system matrices are finally estimated from the above estimated matrices. The consistency of the proposedmethod for estimation of the extended observability matrix and the triangular block-Toeplitz matrix is established. Compared with the classical SIMs using parity space like SIMPCA and SIMPCA-Wc, the proposed method generallyenhances the estimated model efficiency/accuracy thanks to the use of future input data. Two examples arepresented to illustrate the effectiveness and merit of the proposed method.
In this paper, an alternative consistent subspace identification method using parity space is proposed. The future/past input data and the past output data are used to construct the instrument variable to eliminate thenoise effect on consistent estimation. The extended observability matrix and the triangular block-Toeplitz matrixare then retrieved from a parity space of the noise-free matrix using a singular value decomposition based method. The system matrices are finally estimated from the above estimated matrices. The consistency of the proposedmethod for estimation of the extended observability matrix and the triangular block-Toeplitz matrix is established. Compared with the classical SIMs using parity space like SIMPCA and SIMPCA-Wc, the proposed method generallyenhances the estimated model efficiency/accuracy thanks to the use of future input data. Two examples arepresented to illustrate the effectiveness and merit of the proposed method.