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2018 | OriginalPaper | Chapter

Continuous-Time Estimation Filtering with Incorporation of Temporary Model Uncertainty

Author : Pyung Soo Kim

Published in: Advances in Computer Science and Ubiquitous Computing

Publisher: Springer Singapore

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Abstract

In this paper, a continuous-time estimation filtering is developed to incorporate temporary model uncertainty. The infinite memory structure (IMS) estimation filter is applied for the certain system and the finite memory structure (FMS) estimation filter is applied for the temporarily uncertain system, selectively. Therefore, one of two filtered estimates is selected as the valid estimate according to presence or absence of uncertainty. In order to indicate presence or absence of uncertainty and select the valid filtered estimate from IMS and FMS filtered estimates, two test variables and detection rule are defined. Computer simulations show that the proposed continuous-time estimation filter works well for both certain system and temporarily uncertain system.

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Metadata
Title
Continuous-Time Estimation Filtering with Incorporation of Temporary Model Uncertainty
Author
Pyung Soo Kim
Copyright Year
2018
Publisher
Springer Singapore
Book
Advances in Computer Science and Ubiquitous Computing

Print ISBN: 978-981-10-7604-6

Electronic ISBN: 978-981-10-7605-3

Copyright Year: 2018

DOI
https://doi.org/10.1007/978-981-10-7605-3_159