%0 Journal Article
%T DESIGN OF ROBUST RECURSIVE IDENTIFICATION ALGORITHMS FOR LARGE-SCALE STOCHASTIC SYSTEMS
%A Vladimir £¿or£¿evi£¿
%A Vojislav Filipovi£¿
%J -
%D 2015
%X The robust recursive algorithms, for identification of decentralized stochastic systems, are developed. It is supposed that stochastic disturbance belongs to a specified class of distributions which include the gross error model suitable for the description of outliers presence. Such an assumption introduces into the recursive algorithms a nonlinear transformation of prediction error. The given algorithms are robust with respect to uncertainty in the disturbance distribution. The individual subsystems are described with SISO (single-input single output) ARMAX model. Two algorithms are considered: the stochastic approximation and the least squares. Their comparison is based on simulations
%U http://casopisi.junis.ni.ac.rs/index.php/FUAutContRob/article/view/868