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- W2968632384 abstract "Motivated by problems arising in robust control, we develop a sampling-based methodology to obtain an inner approximation of the region of the design space that satisfies a given set of probabilistic constraints (chance constrained set). Given a set of manageable complexity centered at a point satisfying the probabilistic constraints, we show how to scale it around its center to obtain, with a user defined probability, a region that is included in the chance constrained set. The proposed approach does not require any assumption on the Vapnik-Chervonenkis dimension of the robust problem under consideration. Moreover, its sample complexity does not depend on the dimension of the design space. We show the advantages of the proposed approach by means of an illustrative example." @default.
- W2968632384 created "2019-08-22" @default.
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- W2968632384 date "2019-06-01" @default.
- W2968632384 modified "2023-09-30" @default.
- W2968632384 title "Safe approximations of chance constrained sets by probabilistic scaling" @default.
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- W2968632384 doi "https://doi.org/10.23919/ecc.2019.8795669" @default.
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