Journal article
A discontinuous extended kalman filter for non-smooth dynamic problems
- Abstract:
- Problems that result into locally non-differentiable and hence non-smooth state-space equations are often encountered in engineering. Examples include problems involving material laws pertaining to plasticity, impact and highly non-linear phenomena. Estimating the parameters of such systems poses a challenge, particularly since the majority of system identification algorithms are formulated on the basis of smooth systems under the assumption of observability, identifiability and time invariance. For a smooth system, an observable state remains observable throughout the system evolution with the exception of few selected realizations of the state vector. However, for a non-smooth system the observable set of states and parameters may vary during the evolution of the system throughout a dynamic analysis. This may cause standard identification (ID) methods, such as the Extended Kalman Filter, to temporarily diverge and ultimately fail in accurately identifying the parameters of the system. In this work, the influence of observability of non-smooth systems to the performance of the Extended and Unscented Kalman Filters is discussed and a novel algorithm particularly suited for this purpose, termed the Discontinuous Extended Kalman Filter (DEKF), is proposed.
- Publication status:
- Published
- Peer review status:
- Peer reviewed
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(Preview, Accepted manuscript, pdf, 2.1MB, Terms of use)
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- Publisher copy:
- 10.1016/j.ymssp.2017.01.021
Authors
- Publisher:
- Elsevier
- Journal:
- Mechanical Systems and Signal Processing More from this journal
- Volume:
- 92
- Pages:
- 13–29
- Publication date:
- 2017-01-01
- Acceptance date:
- 2017-01-18
- DOI:
- Pubs id:
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pubs:671804
- UUID:
-
uuid:f9989797-87e7-4302-94ab-c9cdc94015e7
- Local pid:
-
pubs:671804
- Source identifiers:
-
671804
- Deposit date:
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2017-01-19
Terms of use
- Copyright holder:
- Elsevier Ltd
- Copyright date:
- 2017
- Notes:
- © 2017 Elsevier Ltd. All rights reserved.
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