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
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;
Conference_Titel :
Control Conference (ECC), 2009 European
Conference_Location :
Budapest
Print_ISBN :
978-3-9524173-9-3
