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Intelligent Automation System for Optimization of Control of Phase States Forecasting of Discrete-Time Dynamical Systems Full article

Journal Lecture Notes in Networks and Systems
ISSN: 2367-3370 , E-ISSN: 2367-3389
Output data Year: 2025, Volume: 1531, Pages: 310-320 Pages count : 11 DOI: 10.1007/978-3-031-98304-7_36
Tags discrete-time dynamical systems; optimization of program control;·forecasting problems; minimax estimation; intelligent control systems
Authors Shorikov Andrey F. 1,2
Affiliations
1 N.N. Krasovskii Institute of Mathematics and Mechanics of the Ural Branch of the Russian Academy of Sciences
2 Institute of Economics of the Ural Branch of the Russian Academy of Sciences

Funding (1)

1 Министерство науки и высшего образования РФ 0327-2024-0010

Abstract: The article considers an intelligent automation system for optimization of the control process of forecasting the phase states of a linear discrete-time dynamical systems. The objective function of the control process estimates the guaranteed (minimax) result of forecasting the admissible states of the phase vector of the system object. For the process under study, the formalization of a multi-step problem of minimax estimation of the forecasting phase states of the system object in a given period of time. The solution to this problem is described in the form of a technique that allows for the implementation of intelligent automation of optimization of forecasting control process. The proposed technique is implemented as a finite sequence of one-step operations that allow their algorithmization. The results obtained in the article can be used in the development and creation of intelligent computer systems for optimizing the control of complex technical and socio-economic dynamical objects.
Cite: Shorikov A.F.
Intelligent Automation System for Optimization of Control of Phase States Forecasting of Discrete-Time Dynamical Systems
Lecture Notes in Networks and Systems. 2025. V.1531. P.310-320. DOI: 10.1007/978-3-031-98304-7_36 OpenAlex
Dates:
Submitted: Jun 9, 2025
Accepted: Jul 10, 2025
Published print: Jul 28, 2025
Published online: Jul 28, 2025
Identifiers:
OpenAlex: W4412675341
Citing: Пока нет цитирований
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