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PresentationsSoft control of a non-linear economic systemFinancial University under the Government of the Russian Federation, 49/2 Leningradsky Ave., Moscow, 125167, Russia Many models of economic cycles are known. There are works where various stochastic perturbations can occur in cycles. Accordingly, depending on the goals, some control is selected for adequate stochastic processing. Such perturbations are used to model systems that are based on economic assumptions that allow for uncertainty in the interaction of system elements. Sometimes it is more expedient to choose fuzzy calculations when the model implies such uncertainty that makes it difficult or impossible to use the apparatus of probability theory to build a satisfactory control. In this paper, a dynamic model of an economic system with a factor subject to uncertainty is investigated. The system is managed through government influence. Control algorithms, including those with fuzzy logic, are proposed based on expert knowledge of R. Goodwin's nonlinear model. A comparative analysis of the proposed algorithms is carried out. Certain advantages of soft control have been identified. The results of the study will be useful for the development of control algorithms in other models not only of a similar class, but also in models of higher dimension. An algorithm has been developed to provide a proportionate response to emerging disturbances. Soft methods allowed not only to increase the "lifetime" of the economic system, but also to reduce the use of public funds. The results obtained may also be of interest when it is necessary to implement state regulation of the economic system with limited reserves.
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