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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| Format: | Article |
| Language: | English |
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Igor Sikorsky Kyiv Polytechnic Institute
2025-02-01
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| Series: | Adaptivni Sistemi Avtomatičnogo Upravlinnâ |
| Subjects: | |
| Online Access: | https://asac.kpi.ua/article/view/323685 |
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| Summary: | 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.
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| ISSN: | 1560-8956 2522-9575 |