  This paper presents a recursive system identification method for
multi-degree-of-freedom (MDoF) structures with tuned mass dampers (TMDs)
considering abrupt stiffness changes in case of sudden events, such as
earthquakes. Due to supplementary non-classical damping of the TMDs, the system
identification of MDoF+TMD systems disposes a challenge, in particular, in case
of sudden events. This identification methods may be helpful for structural
health monitoring of MDoF structures controlled by TMDs. A new adaptation
formulation of the unscented Kalman filter allows the identification method to
track abrupt stiffness changes. The paper, firstly, describes the theoretical
background of the proposed system identification method and afterwards presents
three parametric studies regarding the performance of the method. The first
study shows the augmented state identification by the presented system
identification method applied on a MDoF+TMD system. In this study, the abrupt
stiffness changes of the system are successfully detected and localized under
earthquake, impulse and white noise excitations. The second study investigates
the effects of the state covariance and its relevance for the system
identification of MDoF+TMD systems. The results of this study show the
necessity of an adaptive definition of the state covariance as applied in the
proposed method. The third study investigates the effects of modeling on the
performance of the identification method. Mathematical models with
discretization of different orders of convergence and system noise levels are
studied. The results show that, in particular, MDoF+TMD systems require higher
order mathematical models for an accurate identification of abrupt changes.
