On the choice of inputs in identification for robust control
The thesis that noisy identification has close ties to the study of the singular-value decomposition of perturbed matrices is investigated. In particular by assuming an upper bound on the norm of the perturbation, one can obtain a convex parametrization of an uncertain family of systems which contains the system generating the data. In this approach, the second-smallest singular value σ* of an appropriately defined data matrix becomes a quantity of importance as it provides an upper bound for...[Show more]
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