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Comparison of different approaches for robust identification of a lightly damped flexible beam

The aim of this paper is robust identification of a lightly damped flexible beam model with parametric and non-parametric uncertainties. We examined two main approaches for robust identification which are based on deterministic and stochastic assumptions on uncertainties. In the first case uncertainties are assumed to be unknown but bounded which is known as “Set Membership” method (SM), while stochastic assumptions lead to the so-called “Stochastic Embedding” method (NSSE). 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 modelling techniques will result in superior results.