Abstract: The subject of the research are approaches to the identification of structurally distributed and complex non-stationary technological objects of automated control. The object of study is a non-stationary automated control system. The authors consider in detail the approach of domain identification of objects of automated control based on key (control) points. Special attention is paid to the issues of determining the adequacy of the model for a non-stationary object of automated control. The proposed approach allows iteratively correcting (refining) the object model upon the occurrence of control points (significant changes in the parameters of a multifactorial environment). The main methods of research were used elements of system analysis, natural-mathematical modeling. Additionally, known identification methods were used, incl. using test influences and conversion math models. The main conclusion of the study is the statement that a complex non-stationary technological object cannot be adequately described by a single mathematical model, therefore the identification of such an object must be done several times. The novelty of the research lies in the use of new elements of the domain identification of non-stationary technological objects at the control points, which allows adapting the control to the conditions for changing the multi-factor environment.

Abstract: Managing complex non-stationary systems is a non-trivial task. One of the conditions for effective control is the need to change and adjust the control algorithms under the changing operating conditions of automated systems. The article deals with the construction of control devices based on models of graph theory. As an object of research, approaches and methods of managing complex non-stationary systems are used. An approach based on the domain classification of the factors affecting the control object is considered. Management is considered with significant changes in environmental factors. As simulation methods, simulation and computer modeling were used, which allowed to evaluate the effectiveness of the proposed approaches and management methods. Also, methods of system analysis and modern algorithms on graphs were applied. The presented approach allows to take into account the changing behavior of the non-stationary control object when it is known that certain parameters and factors of the environment can influence this control. The mechanism of the finite state machine allows automatic switching of control algorithms depending on the situation. Studies have shown the expediency of using the proposed approach for the management of complex non-stationary automation systems.