Reduced-order Local Representation of Uncertain Large-scale Interconnected Systems

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Conference Proceeding
Proc. of 2012 American Control Conference, 2012, pp. 2295 - 2300
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We address the structure-preserving model reduction problem of uncertain large-scale systems. The uncertainties under consideration include local uncertainty and interconnection uncertainty, both of which are modeled in terms of IQCs. The performance of the reducedorder system is justified in HÂ¥ sense. It is shown that the feasibility of a collection of rank constrained LMIs is both sufficient and necessary for the existence of a reduced-order representation of the original system. A guaranteed upper bound on the worst-case model reduction performance is also obtained. To obtain a reducedorder model satisfying this bound, related optimization problems involving rank constrained LMIs are discussed.
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