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Robust identification of a lightly damped flexible beam using set-membership and model error modeling techniques

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Abstract

The aim of this paper is robust identification of a lightly damped flexible beam model with parametric and non-parametric uncertainties. Our approach is based on worst case estimation theory where uncertainties are assumed to be unknown but bounded. We examine different outbounding algorithms (parallelotopic and ellipsoidal) for estimation of the feasible parameter set that has been delivered by the set membership identification algorithm. In order to proper handling with the high magnitude non-parametric uncertainties the proposed methods are compared and it is shown that the combination of set membership approach with model error modeling techniques will result in superior results.