A multiplicative regularized Gauss-Newton method with trust region Sequential Quadratic Programming for structural model updating

•A new method for sensitivity-based model updating is proposed.•Ill-conditioning is mitigated by a multiplicative regularization approach.•A trust region Sequential Quadratic Programming with bound constraints is used.•The size of the trust region is a parameter of the regularization functional.•The...

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Veröffentlicht in:	Mechanical systems and signal processing Jg. 131; S. 417 - 433
Hauptverfasser:	Mazzotti, Matteo, Mao, Qiang, Bartoli, Ivan, Livadiotis, Stylianos
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Berlin Elsevier Ltd 15.09.2019 Elsevier BV
Schlagworte:	Algorithms Bridge piers Convexity Gauss-Newton method Ill-conditioned problems (mathematics) Inverse problem Iterative methods Modal analysis Model updating Multiplicative regularization Newton methods Noise pollution Quadratic programming Regularization Sequential Quadratic Programming Stiffness Multiplicative regularization Modal analysis Model updating Inverse problem Sequential Quadratic Programming
ISSN:	0888-3270, 1096-1216
Online-Zugang:	Volltext
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