Combining Convex-Concave Decompositions and Linearization Approaches for Solving BMIs, With Application to Static Output Feedback

A novel optimization method is proposed to minimize a convex function subject to bilinear matrix inequality (BMI) constraints. The key idea is to decompose the bilinear mapping as a difference between two positive semidefinite convex mappings. At each iteration of the algorithm the concave part is l...

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Vydáno v:IEEE transactions on automatic control Ročník 57; číslo 6; s. 1377 - 1390
Hlavní autoři: Quoc Tran Dinh, Gumussoy, S., Michiels, W., Diehl, M.
Médium: Journal Article
Jazyk:angličtina
Vydáno: New York, NY IEEE 01.06.2012
Institute of Electrical and Electronics Engineers
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
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ISSN:0018-9286, 1558-2523
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Shrnutí:A novel optimization method is proposed to minimize a convex function subject to bilinear matrix inequality (BMI) constraints. The key idea is to decompose the bilinear mapping as a difference between two positive semidefinite convex mappings. At each iteration of the algorithm the concave part is linearized, leading to a convex subproblem. Applications to various output feedback controller synthesis problems are presented. In these applications, the subproblem in each iteration step can be turned into a convex optimization problem with linear matrix inequality (LMI) constraints. The performance of the algorithm has been benchmarked on the data from the COMPl e ib library.
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ISSN:0018-9286
1558-2523
DOI:10.1109/TAC.2011.2176154