Convex Necessary and Sufficient Conditions for Model (1n)Validation under SLTV Structured Uncertainty
نویسنده
چکیده
This paper deals with the problem of model (in)validation of discrete-time, causal, LTI stable models subject to Slowly Linear Time Varying structured uncertainly, using freqnency-domain data corrupted by additive noise. It is nell known that in the case of structured LTI uncertainty the problem is NP hard in the number of uncertainty blocks. The main contribution of this paper shows that, on the other hand, if one considers arbitrarily slowly time varying uncertainty and noise in U;, then tractable, convex necessary and sufficient conditions for (in)validation can be obtained.
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