We found a match
Your institution may have access to this item. Find your institution then sign in to continue.
- Title
Unscented Kalman filtering for nonlinear structural dynamics.
- Authors
Stefano Mariani; Aldo Ghisi
- Abstract
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.
- Subjects
CONTROL theory (Engineering); ESTIMATION theory; KALMAN filtering; STOCHASTIC processes
- Publication
Nonlinear Dynamics, 2007, Vol 49, Issue 1/2, p131
- ISSN
0924-090X
- Publication type
Academic Journal
- DOI
10.1007/s11071-006-9118-9