Abstract
AbstractFrequency domain system identification is widely used in the area of structural dynamic analysis. However, due to modeling errors, disturbances and measurement noise, the identified model may be unstable. In this paper, we propose two algorithms to identify structural dynamics with prior knowledge of stable poles. The first algorithm is based on subspace identification, and the second algorithm is based on maximum likelihood in the frequency domain. The corn difference with previous methods in that the new algorithms consider the poles constraint. We show the benefits of the proposed approaches in a simple example where the results of the first algorithm are used as an initial estimate for the second algorithm.
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