- Title
- Identification of continuous-time state-space models from non-uniform fast-sampled data
- Creator
- Yuz, J. I.; Alfaro, J.; Agüero, J. C.; Goodwin, G. C.
- Relation
- IET Control Theory and Applications Vol. 5, Issue 7, p. 842-855
- Publisher Link
- http://dx.doi.org/10.1049/iet-cta.2010.0246
- Publisher
- The Institution of Engineering and Technology
- Resource Type
- journal article
- Date
- 2011
- Description
- In this study, we apply the expectation-maximisation (EM) algorithm to identify continuous-time state-space models from non-uniformly fast-sampled data. The sampling intervals are assumed to be small and uniformly bounded. The authors use a parameterisation of the sampled-data model in incremental form in order to modify the standard formulation of the EM algorithm for discrete-time models. The parameters of the incremental model converge to the parameter of the continuous-time system description as the sampling period goes to zero. The benefits of the proposed algorithm are successfully demonstrated via simulation studies.
- Subject
- state-space methods; expectation-maximisation algorithm; discrete time systems
- Identifier
- http://hdl.handle.net/1959.13/1065853
- Identifier
- uon:17964
- Identifier
- ISSN:1751-8644
- Language
- eng
- Reviewed
- Hits: 2602
- Visitors: 2818
- Downloads: 0
Thumbnail | File | Description | Size | Format |
---|