SOFT CONTROL OF A NON-LINEAR ECONOMIC SYSTEM 

Ivan V. Trundaev, Postgraduate student of the sub-department of mathematics and data analysis, Financial University under the Government of the Russian Federation  (49/2 Leningradsky avenue, Moscow, Russia), ivan_t98@mail.ru

Background. The paper considers the problem of managing an economic system represented by a nonlinear model under conditions of uncertainty. Materials and methods. The economic system is described by a nonlinear model that includes a random factor and a controlling influence from the state. Within the framework of this model, expert knowledge-based management algorithms are built to ensure balanced and sustainable development. Results. A study of the proposed dynamic model describing cycles in the economy and a comparative analysis of the control algorithm using precise and fuzzy control algorithms are carried out. Conclusions. Certain advantages of the proposed fuzzy control algorithm for a nonlinear model based on expert knowledge are highlighted, which can be useful in developing control systems of higher dimension, where the use of classical methods may not be sufficiently justified or appropriate.

nonlinear model, soft control, fuzzy logic, fuzzy sets, regulation in economics, expert systems

Trundaev I.V. Soft control of a non-linear economic system. Modeli, sistemy, seti v ekonomike, tekhnike, prirode i obshchestve = Models, systems, networks in economics,
technology, nature and society. 2025;(1):84–100. (In Russ.). doi: 10.21685/2227-8486-2025-1-7