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Please use this identifier to cite or link to this item: http://bura.brunel.ac.uk/handle/2438/3134

Title: Sampled-data filtering with error covariance assignment
Authors: Wang, Z
Huang, B
Huo, P
Keywords: Continuous-time systems
Discrete-time systems
Sampled-date filtering
Intersample behavior
Kalman filtering
Publication Date: 2001
Publisher: IEEE
Citation: IEEE Transactions on Signal Processing, 49(3): 666-670
Abstract: We consider the sampled-data filtering problem by proposing a new performance criterion in terms of the estimation error covariance. An innovation approach to sampled-data filtering is presented. First, the definition of the estimation covariance e for a sampled-data system is given, then the sampled-data filtering problem is reduced to the Kalman filter design problem for a fictitious discrete-time system, and finally, an effective method is developed to design discrete-time Kalman filters in such a way that the resulting sampled-data estimation covariance achieves a prescribed value. We derive both the existence conditions and the explicit expression of the desired filters and provide an illustrative numerical example to demonstrate the directness and flexibility of the present design method
Description: Copyright [2001] IEEE. 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 Brunel University'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.
URI: http://bura.brunel.ac.uk/handle/2438/3134
ISSN: 1053-587X
Appears in Collections:School of Information Systems, Computing and Mathematics Research Papers
Computer Science

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