Parametric Identification by Means of Consequent Formation of a Conformed Estimations Set

The article proposes an algorithm of parametric identification based on the principle of estimation conformity. The main idea is to form all possible estimations on lesser dimension subsystems, then the densest cloud of the estimations is determined. This cloud is used to find the required solution. We introduce a criterion that takes into account both mutual proximity of estimations and their quantity.