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Communication Dans Un Congrès Année : 2014

Convex Hierarchical Analysis for the Performances of Uncertain Large-Scale Systems

Résumé

The performance analysis of uncertain large-scale systems is considered in this paper. It is performed via a hierarchical modeling and analysis of the systems thanks to the recursive application of a propagation of dissipativity properties result. At each step of the analysis, the local part of the system is viewed as the interconnection of sub-systems. The propagation is used to obtain 'propagated' dissipativity properties of this local part from 'sub' dissipativity properties of the sub-systems. At the next step, the former 'propagated' properties are used as 'sub' properties. This is in contrast with an one-step approach such as (upper bound) µ-analysis which computation time can be prohibitive for large-scale systems even if the associated optimization problem is convex: the trade-off between conservatism and computation time is not necessarily adapted. The purpose is then to obtain a trade-off suited to large-scale systems, an interesting feature being that the trade-off can be set by the user. The approach is used on a PLL network example and illustrates the new trade-off achieved.
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Dates et versions

hal-01089428 , version 1 (01-12-2014)
hal-01089428 , version 2 (29-07-2015)

Identifiants

Citer

M Dinh, Anton Korniienko, Gérard Scorletti. Convex Hierarchical Analysis for the Performances of Uncertain Large-Scale Systems. 53rd IEEE CDC, Dec 2014, Los Angeles, CA, United States. ⟨10.1109/CDC.2014.7040325⟩. ⟨hal-01089428v2⟩
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