Most identification methods of unknown parameters of linear regression
equations (LRE) ensure only boundedness of a parametric error in the presence
of additive perturbations, which is almost always unacceptable for practical
scenarios. In this paper, a new identification law is proposed to overcome this
drawback and guarantee asymptotic convergence of the unknown parameters
estimation error to zero in case the mentioned additive perturbation meets
special averaging conditions. Theoretical results are illustrated by numerical
simulations.Comment: 6 pages, 6 figure