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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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Publisher copy:
10.1016/j.ymssp.2017.01.021

Authors


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Institution:
University of Oxford
Division:
MPLS
Department:
Engineering Science
Role:
Author


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:
pubs:671804
UUID:
uuid:f9989797-87e7-4302-94ab-c9cdc94015e7
Local pid:
pubs:671804
Source identifiers:
671804
Deposit date:
2017-01-19

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