Alternatives with stronger convergence than coordinate-descent iterative LMI algorithms

Fuente: arXiv
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Main Authors: Simon, Emile, Wertz, Vincent
Format: Preprint
Published: 2011
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author Simon, Emile
Wertz, Vincent
author_facet Simon, Emile
Wertz, Vincent
contents In this note we aim at putting more emphasis on the fact that trying to solve non-convex optimization problems with coordinate-descent iterative linear matrix inequality algorithms leads to suboptimal solutions, and put forward other optimization methods better equipped to deal with such problems (having theoretical convergence guarantees and/or being more efficient in practice). This fact, already outlined at several places in the literature, still appears to be disregarded by a sizable part of the systems and control community. Thus, main elements on this issue and better optimization alternatives are presented and illustrated by means of an example.
format Preprint
id arxiv_https___arxiv_org_abs_1110_2615
institution arXiv
publishDate 2011
record_format arxiv
spellingShingle Alternatives with stronger convergence than coordinate-descent iterative LMI algorithms
Simon, Emile
Wertz, Vincent
Optimization and Control
Systems and Control
In this note we aim at putting more emphasis on the fact that trying to solve non-convex optimization problems with coordinate-descent iterative linear matrix inequality algorithms leads to suboptimal solutions, and put forward other optimization methods better equipped to deal with such problems (having theoretical convergence guarantees and/or being more efficient in practice). This fact, already outlined at several places in the literature, still appears to be disregarded by a sizable part of the systems and control community. Thus, main elements on this issue and better optimization alternatives are presented and illustrated by means of an example.
title Alternatives with stronger convergence than coordinate-descent iterative LMI algorithms
topic Optimization and Control
Systems and Control
url https://arxiv.org/abs/1110.2615