A general synthesis of identification and vibration control of building structures under unknown excitations

Abstract

The synthesis of structural health monitoring with vibration control is cost-effective and beneficial for developing smart structures. In the last decade, some synthetic algorithms have been proposed for combining system identification and vibration control. Among them, an approach has been developed recently for the synthesis of identification and vibration control under unknown excitation. However, these approaches are only suitable when structural measurement/observation equations contain the unknown excitations, which limits the application of this approach. In this paper, a general approach is proposed to tackle this limitation problem. A generalized extended Kalman filtering with unknown input (GEKF-UI) is proposed to circumvent the limitations of previous EKF-UI approaches. The proposed GEKF-UI can simultaneously identify structural system and unknown excitation when structural measurement/observation equations contain or do not contain the unknown excitations. Moreover, data fusion of measured acceleration and displacement responses is adopted to prohibit the drifts in the identified structural state and unknown excitations. Then, the identified structural state is synthesized in real time with the linear-quadratic-Gaussian (LQG) control strategy for optimal semi-active optimal control provided by magneto-rheological (MR) dampers. Some numerical examples for the synthesis of identification and vibration control of buildings subject to unknown external forces or unknown earthquake ground motion are adopted to verify the feasibilities of the proposed approach.