On the choice of inputs in identification for robust control

Authors:
A. C. Antoulas;B. D. O. Anderson
Affiliations:
Department of Electrical and Computer Engineering, Rice University, Houston, TX 77251-1892, USA;Department of Systems Engineering and Cooperative Research Center for Robust and Adaptive Systems, Australian National University, Canberra, ACT 2601, Australia
Venue:
Automatica (Journal of IFAC)
Year:
1999

Citing 4
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Brief paper: Identification and control: Joint input design and H∞ state feedback with ellipsoidal parametric uncertainty via LMIs

Automatica (Journal of IFAC)

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Abstract

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@s"* of an appropriately defined data matrix becomes a quantity of importance as it provides an upper bound for the size of the uncertain family. This yields a new tool leading to the design of input functions which are optimal or persistently exciting from the point of view of identification for robust control.