Forecasting the risks of stability loss for nonlinear supply energy systems

N. Bakhtadze, I. Yadykin, E. Maximov, N. Maximova, A. Chereshko, Y. Vershinin

    Research output: Contribution to journalConference articlepeer-review

    1 Citation (Scopus)
    38 Downloads (Pure)

    Abstract

    The paper presents methods for studying the dynamics of nonlinear processes in relation to assessing the risks of stability loss on the basis of accumulated knowledge about the operation of power supply systems and methods for analyzing power supply modes. The methods are a complex of linear point discrete predictive identification models for a wide class of nonlinear objects, as well as spectral decompositions of Gramians for linear models.

    Original languageEnglish
    Pages (from-to)478-483
    Number of pages6
    JournalIFAC-PapersOnLine
    Volume54
    Issue number1
    Early online date9 Nov 2021
    DOIs
    Publication statusPublished - 2021
    Event17th IFAC Symposium on Information Control Problems in Manufacturing INCOM 2021 - Budapest, Hungary
    Duration: 7 Jun 20219 Jun 2021

    Bibliographical note

    Funding Information:
    1 This work was supported by the Russian Science Foundation, project no. 19-19-00673 and by Russian Foundation for Basic Research, project no. 21-57-53005.

    Publisher Copyright:
    © 2021 The Authors. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0)

    Keywords

    • Associative search models
    • Gramian method
    • Knowledge base
    • Process identification

    ASJC Scopus subject areas

    • Control and Systems Engineering

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