A Finite Step Projective Algorithm for Solving Linear Matrix Inequalities

Robert Orsi*, Mustapha Ait Rami, John B. Moore

*Corresponding author for this work

    Research output: Contribution to journalConference articlepeer-review

    7 Citations (Scopus)

    Abstract

    This paper presents an algorithm for finding feasible solutions of linear matrix inequalities. The algorithm is based on the method of alternating projections (MAP), a classical method for solving convex feasibility problems. Unlike MAP, which is an iterative method that converges asymptotically to a feasible point, the algorithm converges after a finite number of steps. The key computational component of the algorithm is an eigenvalue-eigenvector decomposition which is carried out at each iteration. Computational results for the algorithm are presented and comparisons are made with existing algorithms.

    Original languageEnglish
    Pages (from-to)4979-4984
    Number of pages6
    JournalProceedings of the IEEE Conference on Decision and Control
    Volume5
    Publication statusPublished - 2003
    Event42nd IEEE Conference on Decision and Control - Maui, HI, United States
    Duration: 9 Dec 200312 Dec 2003

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