Unscented Kalman filtering for nonlinear structural dynamics |
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Authors: | Stefano Mariani Aldo Ghisi |
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Institution: | (1) Dipartimento di Ingegneria Strutturale, Politecnico di Milano, Piazza L. da Vinci 32, 20133 Milan, Italy |
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Abstract: | Joint estimation of unknown model parameters and unobserved state components for stochastic, nonlinear dynamic systems is
customarily pursued via the extended Kalman filter (EKF). However, in the presence of severe nonlinearities in the equations
governing system evolution, the EKF can become unstable and accuracy of the estimates gets poor. To improve the results, in
this paper we account for recent developments in the field of statistical linearization and propose an unscented Kalman filtering
procedure. In the case of softening single degree-of-freedom structural systems, we show that the performance of the unscented
Kalman filter (UKF), in terms of state tracking and model calibration, is significantly superior to that of the EKF. |
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Keywords: | Kalman filter Nonlinear structural dynamics Parameter identification Statistical linearization |
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