On the identification of model error through observations of time-varying parameters

P. L. Green, E. Chodora, S. Atamturktur

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

When performing system identification, it can be possible to realise a deficient model (i.e. one that will make low fidelity predictions) that is able to closely represent a set of training data. For example, the parameters of linear dynamical models can often be tuned to realise a close match to training data that was generated from a system with strong nonlinearities. Despite this close match to available data, these same models may make very poor-quality predictions when shifted even slightly from the 'validation domain' (which could, for example, be a specific time window). In this paper we investigate the hypothesis that, by treating our model's parameters as being time-varying, we can identify key weaknesses in a model that would have been difficult to establish using other identification methods that do not consider the potentially time-varying nature of the model's parameters. Specifically, we use an Extended Kalman Filter to 'track' the parameters of a dynamical system, as a time history of training data is analysed. We then illustrate that this approach can reveal important information about the potential deficiencies of a model.

Original languageEnglish (US)
Title of host publicationProceedings of ISMA 2018 - International Conference on Noise and Vibration Engineering and USD 2018 - International Conference on Uncertainty in Structural Dynamics
EditorsD. Moens, W. Desmet, B. Pluymers, W. Rottiers
PublisherKU Leuven - Departement Werktuigkunde
Pages2759-2773
Number of pages15
ISBN (Electronic)9789073802995
StatePublished - Jan 1 2018
Event28th International Conference on Noise and Vibration Engineering, ISMA 2018 and 7th International Conference on Uncertainty in Structural Dynamics, USD 2018 - Leuven, Belgium
Duration: Sep 17 2018Sep 19 2018

Publication series

NameProceedings of ISMA 2018 - International Conference on Noise and Vibration Engineering and USD 2018 - International Conference on Uncertainty in Structural Dynamics

Other

Other28th International Conference on Noise and Vibration Engineering, ISMA 2018 and 7th International Conference on Uncertainty in Structural Dynamics, USD 2018
CountryBelgium
CityLeuven
Period9/17/189/19/18

All Science Journal Classification (ASJC) codes

  • Mechanical Engineering
  • Mechanics of Materials
  • Acoustics and Ultrasonics

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