System Identification of Frames under Seismic Loads

In this paper system identification algorithms are employed to construct appropriate nonlinear models of real structures, undergoing seismic disturbances. A three-story half-scale steel frame of the moment resisting type is modeled as a shear frame. The data for this frame were obtained from the Earthquake Engineering Research Center of the University of California. The restoring forces in this model are assumed to be of the viscous differential type, containing four unknown parameters. The solution of the problem, that is, the identification of state parameters, is sought by nonlinear filtering methods. The invariant imbedding filter is presented as a special case of a novel dynamic programming filter. In a purely experimental fashion, it is shown that the adopted model is identifiable and stable by utlizing simulated and real data. Abundant numerical experiments are performed; some of the results are presented. By adding corrective nonlinear terms to the basic linear model, the predictive ability of the model is demonstrated.