Комбіноване керування імпульсними процесами з різнотемповою дискретизацією в когнітивній карті захворюваності на COVID-19
In this article, a cognitive map (CM) of COVID-19 morbidity in a given region was built. A general linear impulse process (IP) model in the CM was developed and measured, and unmeasured CM node coordinates were defined. The general IP model was decomposed into interrelated subsystems with measurable...
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| Datum: | 2022 |
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| Hauptverfasser: | , |
| Format: | Artikel |
| Sprache: | Englisch |
| Veröffentlicht: |
The National Technical University of Ukraine "Igor Sikorsky Kyiv Polytechnic Institute"
2022
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| Schlagworte: | |
| Online Zugang: | http://journal.iasa.kpi.ua/article/view/269395 |
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| Назва журналу: | System research and information technologies |
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System research and information technologies| Zusammenfassung: | In this article, a cognitive map (CM) of COVID-19 morbidity in a given region was built. A general linear impulse process (IP) model in the CM was developed and measured, and unmeasured CM node coordinates were defined. The general IP model was decomposed into interrelated subsystems with measurable and unmeasurable node coordinates. For the subsystem with measurable node coordinates, multirate sampling of coordinates was conducted, resulting in the development of discrete dynamics models for quickly and slowly measured node coordinates. External controls were selected in IP models based on the possible variation of resources of node coordinates and CM weighting coefficients. IP control laws based on the variation of CM nodes and weight were designed. As a result, recurrent procedures for control generation in closed-loop control subsystems with multirate sampling were formulated. Experimental research on the control subsystems was carried out. It confirmed high efficiency for decreasing COVID-19 morbidity. |
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