An augmented Kalman filter for force identification in structural dynamics
By E. Lourens, Edwin Reynders, Guido De Roeck, Geert Degrande, Geert Lombaert. 2012
475 citations recorded by the source corpus.
Subfields: Civil and Structural Engineering, Control and Systems Engineering, Statistics and Probability
View Paper: https://www.semanticscholar.org/paper/7da51739369e61842834076aa2ee3411d30a594c
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Civil and Structural Engineering
- Geert Lombaert
- Eleni N. Chatzi
- Costas Papadimitriou
- Saeed Eftekhar Azam
- K. V. Nimmen
- Edwin Reynders
- E. Lourens
- Guido De Roeck
In Control and Systems Engineering
- Eleni N. Chatzi
- Costas Papadimitriou
- Savvas P. Triantafyllou
- Geert Lombaert
- M. Chatzis
- Saeed Eftekhar Azam
- J. Hurtado
- Diego A. Alvarez
In Statistics and Probability
- Geert Lombaert
- Eleni N. Chatzi
- Costas Papadimitriou
- K. V. Nimmen
- Saeed Eftekhar Azam
- Guido De Roeck
- E. Lourens
- K. Maes
Citations in the corpus
- A dual Kalman filter approach for state estimation via output-only acceleration measurements (2015, methodology): “[29] have proposed an augmented Kalman filter (AKF) for unknown force identification in structural systems, and concluded that the AKF is prone to numerical instabilities due to un-observability issues of the augmented system matrix.”
- A Discontinuous Extended Kalman Filter for non-smooth dynamic problems (2017, methodology): “Modifications of the Kalman filter that may allow for the simultaneous 45 identification of the input force ([10]) and methods based on observers of similar nature ([11, 12]) are also liable to such effects.”
- Design of sensor networks for instantaneous inversion of modally reduced order models in structural dynamics (2015, methodology): “Consider a steel beam with I-shaped cross section [18].”