Output-only schemes for joint input-state-parameter estimation of linear systems

Abstract

The subject of predicting structural response, for control or fatigue assessment purposes, via output only vibration measurements is an emerging topic of Structural Health Monitoring. The subject of estimation of the states of a partially observed dynamic system within a stochastic framework has been studied by many scientists and there are well developed algorithms to manage both linear and nonlinear state-space models. Dealing with structural systems, the system states comprise the response displacements and velocities at the degrees of freedom of the structure. On one hand, in practical cases it is difficult or sometimes impossible to measure structural displacements and velocities for continuous monitoring purposes. On the other hand, recent developments in highly accurate low consumption wireless MEMS accelerometers permit continuous and accurate acceleration measurements when dealing with structural systems. Dealing with operational conditions the uncertainties stemming from the absence of information on the input force, model inaccuracy and measurement errors render the state estimation a challenging task, with research to achieve a robust solution still in progress. Eftekhar Azam et al. [1] have proposed a novel dual Kalman filter to accomplish the task of joint input-state estimation for linear time invariant systems. In this study, the extension of such a scheme is considered for the joint input-state and parameter estimation of linear systems.