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HYBRID DYNAMIC CONTROL SELECTION ALGORITHM: TWO-LEVEL INTEGRATION OF CLASSICAL MODELS AND FUZZY LOGIC BASED ON BINARY CRITERIA

Aksenov Sergey Gennadievich  (Doctor of Economics, Professor, Ufa University of Science and Technology, Ufa, Russian Federation )

In conditions of uncertainty and incomplete a priori information, traditional management methods lose their effectiveness. A two-level intelligent hybrid system is proposed that combines classical regulation and fuzzy logic in a single adaptive cycle. The first level provides continuous management based on analytical models, the second level generates control actions based on expert rules under uncertainty. The system dynamically switches between methods based on an assessment of data availability and result quality, forming a closed loop with correction. At the same time, each step of the algorithm captures the state of the system, provides feedback and allows you to adjust the knowledge base in real time. The approach is implemented through a formalized knowledge base, complies with the laws of hybridization and ensures stability, fault tolerance and applicability to complex technical facilities.

Keywords:hybrid algorithm; dynamic control selection; fuzzy logic; binary criteria.
 

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Citation link:
Aksenov S. G. HYBRID DYNAMIC CONTROL SELECTION ALGORITHM: TWO-LEVEL INTEGRATION OF CLASSICAL MODELS AND FUZZY LOGIC BASED ON BINARY CRITERIA // Современная наука: актуальные проблемы теории и практики. Серия: Естественные и Технические Науки. -2026. -№01. -С. 42-44 DOI 10.37882/2223-2966.2026.01.03
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