Sequential randomized algorithms for sampled convex optimization

Author

Chamanbaz, Mohammadreza ; Dabbene, Fabrizio ; Tempo, Roberto ; Venkataramanan, Venkatakrishnan ; Qing-Guo Wang

Author_Institution

Data Storage Inst., Singapore, Singapore

fYear

2013

fDate

28-30 Aug. 2013

Firstpage

182

Lastpage

187

Abstract

Motivated by the complexity of solving convex scenario problems in one-shot, two new algorithms for the sequential solution of sampled convex optimization problems are presented, for full constraint satisfaction and partial constraint satisfaction, respectively. A rigorous analysis of the theoretical properties of the algorithms is provided, and the related sample complexity is derived. Extensive numerical simulations for a non-trivial example testify the goodness of the proposed solution.

Keywords

aircraft control; computational complexity; constraint satisfaction problems; convex programming; motion control; multivariable control systems; randomised algorithms; aircraft; convex scenario problem; extensive Monte Carlo simulation; full constraint satisfaction; lateral motion; multivariable model; numerical simulation; partial constraint satisfaction; sample complexity; sampled convex optimization; sequential randomized algorithm; Accuracy; Algorithm design and analysis; Complexity theory; Optimization; Probabilistic logic; Standards; Uncertainty;

fLanguage

English

Publisher

ieee

Conference_Titel

Computer Aided Control System Design (CACSD), 2013 IEEE Conference on

Conference_Location

Hyderabad

Type

conf

DOI

10.1109/CACSD.2013.6663480

Filename

6663480