| 1. |
- 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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| 2. |
- McKelvey, Tomas, et al.
(författare)
-
An Efficient Frequency Domain State-Space Identification Algorithm : Robustness and Stochastic Analyis
- 1994
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Ingår i: Proceedings of the 33rd IEEE Conference on Decision and Control. - Linköping : Linköping University. - 0780319680 ; , s. 3348-3353 vol.4
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Rapport (övrigt vetenskapligt/konstnärligt)abstract
- In this paper we present and analyze a novel algorithm for identifying linear time-invariant discrete time state-space models from frequency response data. The algorithm is noniterative and exactly recovers a true system of order n, if n+2 noise-free uniformly spaced frequency response measurements are given. Analysis show that if the measurements are perturbed with errors upper bounded by ε the identification error will be upper bounded by ε and hence the algorithm is robust. An asymptotic stochastic analysis show, under weak assumptions, that the algorithm is consistent if the measurements are contaminated with noise.
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| 3. |
- McKelvey, Tomas, et al.
(författare)
-
An Efficient Frequency Domain State-Space Identification Algorithm
- 1994
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Ingår i: Proceedings of the 33rd IEEE Conference on Decision and Control. - Linköping : Linköping University. - 0780319680 ; , s. 3359-3364 vol.4
-
Rapport (övrigt vetenskapligt/konstnärligt)abstract
- In this paper we present and analyze a novel algorithm for identifying linear time-invariant discrete time state-space models from frequency response data. The algorithm is noniterative and exactly recovers a true system of order n, if n+2 noise-free uniformly spaced frequency response measurements are given. Analysis show that if the measurements are perturbed with errors upper bounded by ε the identification error will be upper bounded by ε and hence the algorithm is robust. An asymptotic stochastic analysis show, under weak assumptions, that the algorithm is consistent if the measurements are contaminated with noise.
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| 4. |
- 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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| 5. |
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| 6. |
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| 7. |
- McKelvey, Tomas, et al.
(författare)
-
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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| 8. |
- McKelvey, Tomas, et al.
(författare)
-
Subspace Based System Identification with Periodic Excitation Signals
- 1995
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Ingår i: Proceedings of the 3rd European Control Conference. - Amsterdam : Elsevier BV. ; 26:5, s. 349-361
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Konferensbidrag (refereegranskat)abstract
- An identification algorithm for use with data generated by periodic inputs is presented. The algorithm is based on the geometrical properties of the resulting periodic output signal and a state-space model is derived from the signal subspace of a Hankel matrix by means of a singular value decomposition. It is shown that 2n+ 1 noise-free output measurements are required to identify an nth order system. The algorithm is demonstrated to be consistent when the output measurements are corrupted by zero mean noise characterized by decaying covariances. The computational complexity of the algorithm is several orders of magnitude lower than standard methods.
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