Subspace-based methods for the identification of linear time-invariant systems |
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Authors: | Mats Viberg |
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Affiliation: | †Department of Applied Electronics, Chalmers University of Technology, S-412 96 Gothenburg, Sweden |
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Abstract: | Subspace-based methods for system identification have attracted much attention during the past few years. This interest is due to the ability of providing accurate state-space models for multivariable linear systems directly from input-output data. The methods have their origin in classical state-space realization theory as developed in the 1960s. The main computational tools are the QR and the singular-value decompositions. Here, an overview of existing subspace-based techniques for system identification is given. The methods are grouped into the classes of realization-based and direct techniques. Similarities between different algorithms are pointed out, and their applicability is commented upon. We also discuss some recent ideas for improving and extending the methods. A simulation example is included for comparing different algorithms. The subspace-based approach is found to perform competitive with respect to prediction-error methods, provided the system is properly excited. |
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Keywords: | System identification subspace methods parameter estimation multivariable systems instrumental variable methods |
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