Abstract
Subspace methods can identify state space models if only input and output measurements are available. Since no measurements of the states are required and employed, it is not possible to come up with a unique structure, hence the model is only known up to a similarity transform T. Interesting features of the state space identification are the fact that subspace identification allows to determine the suitable model oder as part of the identification process and furthermore, the method is from the very beginning formulated to cover MIMO systems as well. A short history of subspace methods can e.g. be found in the editorial note by Viberg and Stoica (1996).
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Isermann, R., Münchhof, M. (2011). Subspace Methods. In: Identification of Dynamic Systems. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-78879-9_16
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DOI: https://doi.org/10.1007/978-3-540-78879-9_16
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