Model validation: a connection between robust control and identification
Roy S. Smith,John Doyle +1 more
TLDR
The model validation problem addressed is: given experimental data and a model with both additive noise and norm-bounded perturbations, is it possible that the model could produce the observed input-output data?Abstract:
The gap between the models used in control synthesis and those obtained from identification experiments is considered by investigating the connection between uncertain models and data. The model validation problem addressed is: given experimental data and a model with both additive noise and norm-bounded perturbations, is it possible that the model could produce the observed input-output data? This problem is studied for the standard H/sub infinity // mu framework models. A necessary condition for such a model to describe an experimental datum is obtained. For a large class of models in the robust control framework, this condition is computable as the solution of a quadratic optimization problem. >read more
Citations
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l/sub 1/ identification applied to a fluid dynamics problem
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Model falsification using SVOs for a class of discrete-time dynamic systems: A coprime factorization approach
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Accurate $\mathcal{H}_{\infty}$-Norm Estimation via Finite-Frequency Norms of Local Parametric Models
P.J.M.M. Tacx,Tom Oomen +1 more
TL;DR: In this paper, a frequency response-based approach is pursued, and local modeling techniques are exploited to include the inter-grid behavior to estimate the global norm by estimating the finite-frequency L ∞ norm of the local models through the generalized KYP lemma.
References
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