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A lower bound for the mixed µ problem

Young, Peter M. and Doyle, John C. (1997) A lower bound for the mixed µ problem. IEEE Transactions on Automatic Control, 42 (1). pp. 123-128. ISSN 0018-9286. doi:10.1109/9.553696. https://resolver.caltech.edu/CaltechAUTHORS:20190315-100211418

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Abstract

The mixed µ problem has been shown to be NP hard so that exact analysis appears intractable. Our goal then is to exploit the problem structure so as to develop a polynomial time algorithm that approximates µ and usually gives good answers. To this end it is shown that µ is equivalent to a real eigenvalue maximization problem, and a power algorithm is developed to tackle this problem. The algorithm not only provides a lower bound for µ but has the property that µ is (almost) always an equilibrium point of the algorithm.


Item Type:Article
Related URLs:
URLURL TypeDescription
https://doi.org/10.1109/9.553696DOIArticle
ORCID:
AuthorORCID
Doyle, John C.0000-0002-1828-2486
Additional Information:© 1997 IEEE. Manuscript received January 27, 1995. This work was supported by the NSF, ONR, NASA, and Rockwell. The authors would like to thank A. Packard for helpful discussions and M. Newlin for help in implementing the lower-bound software.
Funders:
Funding AgencyGrant Number
NSFUNSPECIFIED
Office of Naval Research (ONR)UNSPECIFIED
NASAUNSPECIFIED
Rockwell InternationalUNSPECIFIED
Subject Keywords:Computational methods, control system analysis, robust control, stability analysis, structured singular value
Issue or Number:1
DOI:10.1109/9.553696
Record Number:CaltechAUTHORS:20190315-100211418
Persistent URL:https://resolver.caltech.edu/CaltechAUTHORS:20190315-100211418
Official Citation:P. M. Young and J. C. Doyle, "A lower bound for the mixed µ problem," in IEEE Transactions on Automatic Control, vol. 42, no. 1, pp. 123-128, Jan. 1997. doi: 10.1109/9.553696
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:93860
Collection:CaltechAUTHORS
Deposited By: Tony Diaz
Deposited On:15 Mar 2019 17:08
Last Modified:16 Nov 2021 17:01

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