Adaptive weighting inverse method for the estimation of input loads

An adaptive weighting input estimation method for estimating the time varying input loads acted on structural systems is presented. The algorithm employs the simple Kalman filter to propose a regression model between the residual innovation and the input loads. Based on this regression equation, a recursive least-squares estimator weighted by an adaptive fading factor is used to estimate on-line the input loads involving measurement noise and modelling errors. The capabilities of the proposed algorithm are demonstrated by numerical experiments to estimate the input loads acting on two lumped-mass systems and a cantilever beam. The estimation results show that the proposed adaptive fading factor improves the eficiency and robustness of the conventional input estimation approach.

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