Modeling and Solving Uncertain Optimization Problems in YALMIP
2008 (English)In: Proceedings of the 17th IFAC World Congress, 2008, 1337-1341 p.Conference paper (Refereed)
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.
Uncertainty descriptions, Robust linear matrix inequalities, Convex optimization
Engineering and Technology Control Engineering
IdentifiersURN: urn:nbn:se:liu:diva-44587DOI: 10.3182/20080706-5-KR-1001.1729Local ID: 77139ISBN: 978-3-902661-00-5OAI: oai:DiVA.org:liu-44587DiVA: diva2:265449
17th IFAC World Congress, Seoul, South Korea, July, 2008