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Modeling and Solving Uncertain Optimization Problems in YALMIP
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
2008 (English)In: Proceedings of the 17th IFAC World Congress, 2008, 1337-1341 p.Conference paper, Published paper (Refereed)
Abstract [en]

A considerable amount of optimization problems arising in the control and systemstheory field can be seen as special instances of robust optimization. Much of the modelingeffort in these cases is spent on converting an uncertain problem to a robust counterpartwithout uncertainty. Since many of these conversions follow standard procedures, it is amenableto software support. This paper presents the robust optimization framework in the modelinglanguage YALMIP, which carries out the uncertainty elimination automatically, and allows theuser to concentrate on the high-level model instead.

Place, publisher, year, edition, pages
2008. 1337-1341 p.
Keyword [en]
Uncertainty descriptions, Robust linear matrix inequalities, Convex optimization
National Category
Engineering and Technology Control Engineering
Identifiers
URN: urn:nbn:se:liu:diva-44587DOI: 10.3182/20080706-5-KR-1001.1729Local ID: 77139ISBN: 978-3-902661-00-5 (print)OAI: oai:DiVA.org:liu-44587DiVA: diva2:265449
Conference
17th IFAC World Congress, Seoul, South Korea, July, 2008
Available from: 2009-10-10 Created: 2009-10-10 Last updated: 2013-02-23

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Löfberg, Johan

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