## Abstract

In this paper, we present preliminary results on a general approach to chance constrained algebraic problems. In this type of problems, one aims at maximizing the probability of a set defined by polynomial inequalities. These problems are, in general, nonconvex and computationally complex. With the objective of developing systematic numerical procedures to solve such problems, a sequence of convex relaxations is provided, whose optimal value is shown to converge to solution of the original problem. In other words, we provide a sequence of semidefinite programs of increasing dimension and complexity which can arbitrarily approximate the solution of the probability maximization problem. Two numerical examples are presented to illustrate preliminary results on the numerical performance of the proposed approach.

Original language | English (US) |
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Article number | 6426305 |

Pages (from-to) | 2527-2532 |

Number of pages | 6 |

Journal | Proceedings of the IEEE Conference on Decision and Control |

DOIs | |

State | Published - Dec 1 2012 |

Event | 51st IEEE Conference on Decision and Control, CDC 2012 - Maui, HI, United States Duration: Dec 10 2012 → Dec 13 2012 |

## All Science Journal Classification (ASJC) codes

- Control and Systems Engineering
- Modeling and Simulation
- Control and Optimization