Experimental validation of the dual Kalman filter for online and real-time state and input estimation

Abstract

In this study, a novel dual implementation of the Kalman filter is proposed for simultaneous estimation of the states and input of structures via acceleration measurements. In practice, the uncertainties stemming from the absence of information on the input force, model inaccuracy and measurement errors render the state estimation a challenging task and the research to achieve a robust solution is still in progress. Via the use of numerical simulation, it was shown that the proposed method outperforms the existing techniques in terms of robustness and accuracy of displacement and velocity estimations [8]. The efficacy of the proposed method is validated using the data obtained from a shake table experiment on a laboratory test structure. The measured accelerations of the floors of the structure are fed into the filter, and the estimated time histories of the displacement estimates are cross-compared to the true time histories obtained from the displacement sensors. © The Society for Experimental Mechanics, Inc. 2015.