An extended model-based observer for state estimation in nonlinear hysteretic structural systems

This paper proposes a model-based observer for state estimation in nonlinear hysteretic structural systems. The observer combines a nonlinear model and response measurements to estimate the complete dynamic response of the structure of interest. The feedback gain of the observer is computed by an iterative algorithm that accounts for the nonlinearity of the system and minimizes the trace of the state error covariance matrix. The main feature of the proposed observer (and its main advantage with respect to existing nonlinear state estimators) is that it is designed to be physically realizable as a nonlinear structural model, which allows the user to benefit from modeling capabilities available in finite element solvers. The performance of the proposed observer is studied in the context of a numerical example consisting of a nonlinear chain model with a Bouc-Wen model of hysteresis subjected to a base motion; the estimation results are compared to those obtained using an unscented Kalman filter. The observer is also validated experimentally using data from a six-story full-scale benchmark wood frame building tested by the NEESWood project at the E-Defense facility in Miki, Japan. The results show the effectiveness of the proposed approach to estimate the dynamic response of large-scale structural systems exhibiting a strong nonlinear behavior. (C) 2020 Elsevier Ltd. All rights reserved.