Semidefinite programming duality and linear time-invariant systems

Several important problems in control theory can be reformulated as semidefinite programming problems, i.e., minimization of a linear objective subject to linear matrix inequality (LMI) constraints. From convex optimization duality theory, conditions for infeasibility of the LMIs, as well as dual op...

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Bibliographic Details
Published in:IEEE transactions on automatic control Vol. 48; no. 1; pp. 30 - 41
Main Authors: Balakrishnan, V., Vandenberghe, L.
Format: Journal Article
Language:English
Published: New York, NY IEEE 01.01.2003
Institute of Electrical and Electronics Engineers
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
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ISSN:0018-9286, 1558-2523
Online Access:Get full text
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Summary:Several important problems in control theory can be reformulated as semidefinite programming problems, i.e., minimization of a linear objective subject to linear matrix inequality (LMI) constraints. From convex optimization duality theory, conditions for infeasibility of the LMIs, as well as dual optimization problems, can be formulated. These can in turn be reinterpreted in control or system theoretic terms, often yielding new results or new proofs for existing results from control theory. We explore such connections for a few problems associated with linear time-invariant systems.
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ISSN:0018-9286
1558-2523
DOI:10.1109/TAC.2002.806652