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arXiv · 1110.2615

Alternatives with stronger convergence than coordinate-descent iterative LMI algorithms

Emile Simon·Vincent Wertz
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Abstract

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.

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Emile Simon, Vincent Wertz. 2011-10-12. Alternatives with stronger convergence than coordinate-descent iterative LMI algorithms. https://arxiv.org/abs/1110.2615

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