DocumentCode
696286
Title
Sample-based minimax linear-quadratic optimization
Author
Siemenikhin, Konstantin ; Pankov, Alexei ; Ignastchenko, Yegor
Author_Institution
Dept. of Probability Theor., Moscow Aviation Inst., Moscow, Russia
fYear
2009
fDate
23-26 Aug. 2009
Firstpage
3221
Lastpage
3226
Abstract
The method of sample-based minimax optimization is developed for the minimization problem with an uncertain quadratic objective function subject to linear constraints. Several examples based on confidence statistical estimation are considered to define the uncertainty set. Analytical and numerical techniques are proposed for finding the optimal robust strategy.
Keywords
linear programming; minimax techniques; minimisation; numerical analysis; quadratic programming; statistical analysis; analytical technique; confidence statistical estimation; linear constraints; minimization problem; numerical technique; optimal robust strategy; sample-based minimax linear-quadratic optimization; uncertain quadratic objective function; uncertainty set; Covariance matrices; Estimation; Optimization; Robustness; Symmetric matrices; Uncertainty; Vectors;
fLanguage
English
Publisher
ieee
Conference_Titel
Control Conference (ECC), 2009 European
Conference_Location
Budapest
Print_ISBN
978-3-9524173-9-3
Type
conf
Filename
7074901
Link To Document