A gain-based lower bound algorithm for real and mixed μ problems

Pete Seiler, Gary Balas, Andrew Packard

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Scopus citations

Abstract

In this paper we present a new lower bound algorithm for real and mixed μ problems. The basic idea of this algorithm is to use a related worst-case gain problem to compute the real blocks and, if the block structure is mixed, the standard power iteration to compute the complex blocks. Initial numerical tests indicate that the algorithm is fast and provides good bounds for both real and mixed μ problems of small to moderate size.

Original languageEnglish (US)
Title of host publicationProceedings of the 45th IEEE Conference on Decision and Control 2006, CDC
Pages3548-3553
Number of pages6
StatePublished - Dec 1 2006
Event45th IEEE Conference on Decision and Control 2006, CDC - San Diego, CA, United States
Duration: Dec 13 2006Dec 15 2006

Publication series

NameProceedings of the IEEE Conference on Decision and Control
ISSN (Print)0191-2216

Other

Other45th IEEE Conference on Decision and Control 2006, CDC
CountryUnited States
CitySan Diego, CA
Period12/13/0612/15/06

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