Archivio Istituzionale della RicercaIn this paper, randomized algorithms for stability and performance of linear time invariant uncertain systems described by a general M-Δ configuration are studied. On the contrary of the worst-case approach, which is often not tractable in the NP-hardness sense, this problem turns out to be solvable in a probabilistic setting. In particular, efficient polynomial-time algorithms for uncertainty structures Δ consisting of an arbitrary number of full complex blocks and uncertain parameters, real or complex and possibly repeated, are developed
Randomized Algorithms for Probabilistic Robustness with Structured Uncertainty / Calafiore, Giuseppe Carlo; Dabbene, F; Tempo, R.. - STAMPA. - 1:(1999), pp. 528-533. (Intervento presentato al convegno 38th IEEE Conference on Decision and Control tenutosi a Phoenix, AZ nel 07-10 Dec 1999) [10.1109/CDC.1999.832836].
Randomized Algorithms for Probabilistic Robustness with Structured Uncertainty
CALAFIORE, Giuseppe Carlo;
1999
Abstract
In this paper, randomized algorithms for stability and performance of linear time invariant uncertain systems described by a general M-Δ configuration are studied. On the contrary of the worst-case approach, which is often not tractable in the NP-hardness sense, this problem turns out to be solvable in a probabilistic setting. In particular, efficient polynomial-time algorithms for uncertainty structures Δ consisting of an arbitrary number of full complex blocks and uncertain parameters, real or complex and possibly repeated, are developed
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https://hdl.handle.net/11583/1408968
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