| 1. |
- Akçay, Hüseyin, et al.
(författare)
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On the Choice of Norms in System Identification
- 1994
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Ingår i: Proceedings of the 10th IFAC Symposium on System Identification. - Linköping : Linköping University. - 9780080422251 ; , s. 103-108
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Rapport (övrigt vetenskapligt/konstnärligt)abstract
- In this paper we discuss smooth and sensitive norms for prediction error system identification when the disturbances are magnitude bounded. Formal conditions for sensitive norms, which give an order of magnitude faster convergence of the parameter estimate variance, are developed. However, it also is shown that the parameter estimate variance convergence rate of sensitive norms is arbitrarily bad for certain distributions. A necessary condition for a norm to be statistically robust with respect to the family F(C) of distributions with support [-C, C] for some arbitrary C>0 is that its second derivative does not vanish on the support. A direct consequence of this observation is that the quadratic norm is statistically robust among all lp-norms, p⩽2<∞ for F(C).
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| 2. |
- Ljung, Lennart, 1946-, et al.
(författare)
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Subspace-based Identification of Infinite-dimensional Multivariable Systems from Frequency-response Data
- 1996
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Ingår i: Automatica. - : Elsevier. - 0005-1098 .- 1873-2836. ; 32:6, s. 885-902
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Tidskriftsartikel (refereegranskat)abstract
- A new identification algorithm which identifies low complexity models of infinite-dimensional systems from equidistant frequency-response data is presented. The new algorithm is a combination of the Fourier transform technique with the recent subspace techniques. Given noisefree data, finite-dimensional systems are exactly retrieved by the algorithm. When noise is present, it is shown that identified models strongly converge to the balanced truncation of the identified system if the measurement errors are covariance bounded. Several conditions are derived on consistency, illustrating the trade-offs in the selection of certain parameters of the algorithm. Two examples are presented which clearly illustrate the good performance of the algorithm.
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| 3. |
- McKelvey, Tomas, 1966-, et al.
(författare)
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Efficient Construction of Transfer Functions from Frequency Response Data
- 1994
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Rapport (övrigt vetenskapligt/konstnärligt)abstract
- In this paper, we present a novel non-iterative algorithm to identify linear time-invariant systems from frequency response data. The algorithm is related to the recent time-domain subspace identification techniques. Promising results are obtained when the algorithm is applied to the real frequency data originating from a large flexible structure. A robustness analysis is performed and under weak conditions on the measurement noise, it is shown that the algorithm is consistent.
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| 4. |
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| 5. |
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| 6. |
- McKelvey, Tomas, et al.
(författare)
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Subspace-Based Multivariable System Identification from Frequency Response Data
- 1996
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Ingår i: IEEE Transactions on Automatic Control. - : Institute of Electrical and Electronics Engineers (IEEE). - 0018-9286 .- 1558-2523. ; 41:7, s. 960-979
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Tidskriftsartikel (refereegranskat)abstract
- Two noniterative subspace-based algorithms which identify linear, time-invariant MIMO (multi-input/multioutput) systems from frequency response data are presented. The algorithms are related to the recent time-domain subspace identification techniques. The first algorithm uses equidistantly, in frequency, spaced data and is strongly consistent under weak noise assumptions. The second algorithm uses arbitrary frequency spacing and is strongly consistent under more restrictive noise assumptions, promising results are obtained when the algorithms are applied to real frequency data originating from a large flexible structure.
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