- Title
- A continuous-time linear system identification method for slowly sampled data
- Creator
- Marelli, Damián; Fu, Minyue
- Relation
- IEEE Transactions on Signal Processing Vol. 58, Issue 5, p. 2521-2533
- Publisher Link
- http://dx.doi.org/10.1109/tsp.2009.2040017
- Publisher
- Institute of Electrical and Electronics Engineers (IEEE)
- Resource Type
- journal article
- Date
- 2010
- Description
- Both direct and indirect methods exist for identifying continuous-time linear systems. A direct method estimates continuous-time input and output signals from their samples and then use them to obtain a continuous-time model, whereas an indirect method estimates a discrete-time model first. Both methods rely on fast sampling to ensure good accuracy. In this paper, we propose a more direct method where a continuous-time linear model is directly fitted to the available samples. This method produces an exact model asymptotically, modulo some possible aliasing ambiguity, even when the sampling rate is relatively slow.We also state conditions under which the aliasing ambiguity can be resolved, and we provide experiments showing that the proposed method is a valid option when a slow sampling frequency must be used but a large number of samples is available.
- Subject
- continuous time systems; identification; parameter estimation; sampled data systems.
- Identifier
- http://hdl.handle.net/1959.13/928893
- Identifier
- uon:10471
- Identifier
- ISSN:1053-587X
- Rights
- Copyright © 2010 IEEE. Reprinted from IEEE Transactions on Signal Processing. This material is posted here with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of the University of Newcastle's products or services. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to pubs-permissions@ieee.org. By choosing to view this document, you agree to all provisions of the copyright laws protecting it.
- Language
- eng
- Full Text
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