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article · 2012

An Ellipsoid Algorithm for linear optimization with uncertain LMI constraints

Armin Ataei, Qian Wang

Cited by 3Abstract and details only

Abstract

In this paper, an efficient algorithm based on the ellipsoid method is proposed to solve a linear optimization problem over a set of uncertain Linear Matrix Inequalities (LMIs). First, an Ellipsoid Algorithm (EA) with deep cuts is introduced for solving the set of uncertain LMIs. The proposed ellipsoid algorithm is shown to converge to a probabilistically feasible point with high confidence level and in fewer iterations compared to other EA methods. Then, through a set of new cuts, the objective function is minimized while maintaining the probabilistic feasibility of the solution.

Cite this paper

APA 7

Ataei, A., & Wang, Q. (2012). An Ellipsoid Algorithm for linear optimization with uncertain LMI constraints. https://doi.org/10.1109/acc.2012.6315611

MLA 9

Ataei, Armin, and Qian Wang. “An Ellipsoid Algorithm for linear optimization with uncertain LMI constraints.” 2012, https://doi.org/10.1109/acc.2012.6315611.

Chicago

Ataei, Armin, and Qian Wang. 2012. “An Ellipsoid Algorithm for linear optimization with uncertain LMI constraints.” https://doi.org/10.1109/acc.2012.6315611.

Harvard

Ataei, A. and Wang, Q. (2012) ‘An Ellipsoid Algorithm for linear optimization with uncertain LMI constraints’. Available at: https://doi.org/10.1109/acc.2012.6315611.

BibTeX
@article{ataei2012ellipsoid,
  title = {{An Ellipsoid Algorithm for linear optimization with uncertain LMI constraints}},
  author = {Ataei, Armin and Wang, Qian},
  year = {2012},
  doi = {10.1109/acc.2012.6315611}
}

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