
This paper deals with the problem of identifying multivariable finite dimensional linear time-invariant systems from noisy input/output measurements. A solution is obtained by means of subspace identification algorithms. Some SMI algorithms that consistently estimate state space models are presented. They allow to solve identification problems via inspection of singular values. Two realistic simulation studies are presented.
consistency, subspace identification algorithms, System identification, instrumental variable methods
consistency, subspace identification algorithms, System identification, instrumental variable methods
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