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Frequency weighted subspace based system identification in the frequency domain (1995).
| Content Provider | CiteSeerX |
|---|---|
| Author | Mckelvey, Tomas |
| Abstract | Frequency weighting capabilities are introduced in a recent subspace based frequency domain identification algorithm [8]. Weighting matrices constructed from the impulse response of weighting filters are used to weight a Hankel matrix prior of deriving the signal subspace by the singular value decomposition. The resulting algorithm is shown to asymptotically produce models which are frequency weighted balanced. An illustrative example shows the applicability of the method for finite data. Keywords: Identification; Subspace Method; Frequency Weighting; Model Reduction; Singular Value Decomposition. 1 Introduction In most practical identification applications it is important to be able to shape the resulting identification error. Often prior information is available which can be used to improve the model quality. A most common knowledge is the frequency content used in the excitation and the spectral density of the noise sources. For identification in the time domain this is accomplishe... |
| File Format | |
| Publisher Date | 1995-01-01 |
| Access Restriction | Open |
| Subject Keyword | Subspace Based System Identification Frequency Domain Singular Value Decomposition Identification Error Recent Subspace Noise Source Spectral Density Practical Identification Application Frequency Domain Identification Model Quality Subspace Method Impulse Response Frequency Weighting Illustrative Example Signal Subspace Hankel Matrix Model Reduction Frequency Content Often Prior Information Common Knowledge Finite Data Time Domain |
| Content Type | Text |
