TY - JOUR
T1 - Sensitivity-based model updating with parameter rejection
AU - Ulriksen, Martin Dalgaard
AU - Bernal, Dionisio
PY - 2025/6
Y1 - 2025/6
N2 - Sensitivity-based model updating entails a computational parameter estimation problem, in which a set of model parameters is adjusted to minimize the discrepancy between identified system features and the corresponding model predictions. In order to promote the posedness and conditioning of the estimation problem, it is often necessary to exclude some of the uncertain parameters and accept the errors induced by treating them at their nominal values. The present paper proposes a parameter rejection scheme that seeks to mitigate the noted errors by minimizing the sensitivity of the estimation problem to changes in the excluded parameters. The sensitivity minimization is realized in a closed-loop setting with output feedback eigenstructure assignment, which, given that the operation is offline, can be implemented through processing of open-loop input-output data. Consequently, the scheme rests on the assumption that open-loop input-output data can be collected while the considered system is linear and time-invariant. The implementation and validity of the scheme are demonstrated in the context of numerical and experimental examples with vibrating systems.
AB - Sensitivity-based model updating entails a computational parameter estimation problem, in which a set of model parameters is adjusted to minimize the discrepancy between identified system features and the corresponding model predictions. In order to promote the posedness and conditioning of the estimation problem, it is often necessary to exclude some of the uncertain parameters and accept the errors induced by treating them at their nominal values. The present paper proposes a parameter rejection scheme that seeks to mitigate the noted errors by minimizing the sensitivity of the estimation problem to changes in the excluded parameters. The sensitivity minimization is realized in a closed-loop setting with output feedback eigenstructure assignment, which, given that the operation is offline, can be implemented through processing of open-loop input-output data. Consequently, the scheme rests on the assumption that open-loop input-output data can be collected while the considered system is linear and time-invariant. The implementation and validity of the scheme are demonstrated in the context of numerical and experimental examples with vibrating systems.
KW - Model updating
KW - Parameter estimation and rejection
KW - eigenstructure assignment
U2 - 10.1016/j.apm.2025.116253
DO - 10.1016/j.apm.2025.116253
M3 - Journal article
SN - 0307-904X
VL - 148
JO - Applied Mathematical Modelling
JF - Applied Mathematical Modelling
M1 - 116253
ER -