Cybernetic approaches to adaptive control of supercritical systems

This paper introduces an adaptive control framework for stabilizing supercritical systems near critical stability thresholds, where conventional methods fail due to nonlinear dynamics and interdependencies. The proposed method integrates real-time feedback, predictive modeling, and reliability anal...

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Main Author: Д. Гуменний
Format: Article
Language:English
Published: Igor Sikorsky Kyiv Polytechnic Institute 2025-02-01
Series:Adaptivni Sistemi Avtomatičnogo Upravlinnâ
Subjects:
Online Access:https://asac.kpi.ua/article/view/323685
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author Д. Гуменний
author_facet Д. Гуменний
author_sort Д. Гуменний
collection DOAJ
description This paper introduces an adaptive control framework for stabilizing supercritical systems near critical stability thresholds, where conventional methods fail due to nonlinear dynamics and interdependencies. The proposed method integrates real-time feedback, predictive modeling, and reliability analysis using Bayesian updates and Weibull distribution, enhancing resilience under unpredictable conditions. A dual-layered model combines deterministic feedback for structural control and stochastic reliability assessments for managing uncertainty. This approach is crucial for fields like robotics and industrial automation, ensuring stability, scalability, and fault tolerance in high-risk environments. Ref. 12
format Article
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institution DOAJ
issn 1560-8956
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language English
publishDate 2025-02-01
publisher Igor Sikorsky Kyiv Polytechnic Institute
record_format Article
series Adaptivni Sistemi Avtomatičnogo Upravlinnâ
spelling doaj-art-e4efbd533f1f4508a71d54449f7d0ae52025-08-20T03:17:15ZengIgor Sikorsky Kyiv Polytechnic InstituteAdaptivni Sistemi Avtomatičnogo Upravlinnâ1560-89562522-95752025-02-0114610.20535/1560-8956.46.2025.323685362460Cybernetic approaches to adaptive control of supercritical systemsД. Гуменний0Igor Sikorsky Kyiv Polytechnic Institute This paper introduces an adaptive control framework for stabilizing supercritical systems near critical stability thresholds, where conventional methods fail due to nonlinear dynamics and interdependencies. The proposed method integrates real-time feedback, predictive modeling, and reliability analysis using Bayesian updates and Weibull distribution, enhancing resilience under unpredictable conditions. A dual-layered model combines deterministic feedback for structural control and stochastic reliability assessments for managing uncertainty. This approach is crucial for fields like robotics and industrial automation, ensuring stability, scalability, and fault tolerance in high-risk environments. Ref. 12 https://asac.kpi.ua/article/view/323685supercritical systemsWeibull distributionLyapunov stabilitycybernetic feedback
spellingShingle Д. Гуменний
Cybernetic approaches to adaptive control of supercritical systems
Adaptivni Sistemi Avtomatičnogo Upravlinnâ
supercritical systems
Weibull distribution
Lyapunov stability
cybernetic feedback
title Cybernetic approaches to adaptive control of supercritical systems
title_full Cybernetic approaches to adaptive control of supercritical systems
title_fullStr Cybernetic approaches to adaptive control of supercritical systems
title_full_unstemmed Cybernetic approaches to adaptive control of supercritical systems
title_short Cybernetic approaches to adaptive control of supercritical systems
title_sort cybernetic approaches to adaptive control of supercritical systems
topic supercritical systems
Weibull distribution
Lyapunov stability
cybernetic feedback
url https://asac.kpi.ua/article/view/323685
work_keys_str_mv AT dgumennij cyberneticapproachestoadaptivecontrolofsupercriticalsystems