SOFT CONTROL OF A NON-LINEAR ECONOMIC SYSTEM

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.

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Publication Details

Journal
Models systems networks in economics technology nature and society
Published
2025-01-01
DOI
https://doi.org/10.21685/2227-8486-2025-1-7
Citations
1
Primary Topic
Economic theories and models
Type
article
Field-Weighted Citation Impact
3.13
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article

SOFT CONTROL OF A NON-LINEAR ECONOMIC SYSTEM

Ivan V. Trundaev
1 citations
Models systems networks in economics technology nature and society
Economic theories and models
3.13
article

SOFT CONTROL OF A NON-LINEAR ECONOMIC SYSTEM

Ivan V. Trundaev
article en
1 citations

Abstract

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.

Models systems networks in economics technology nature and society(1)
Openalex Percentile: Top 8%
Economic theories and models
3.13
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