Analysis and Prediction of Electric Power System’s Stability Based on Virtual State Estimators
Natalia Bakhtadze and
Igor Yadikin
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Natalia Bakhtadze: V.A. Trapeznikov Institute of Control Sciences, 65 Profsoyuznaya, 117997 Moscow, Russia
Igor Yadikin: V.A. Trapeznikov Institute of Control Sciences, 65 Profsoyuznaya, 117997 Moscow, Russia
Mathematics, 2021, vol. 9, issue 24, 1-16
Abstract:
The stability of bilinear systems is investigated using spectral techniques such as selective modal analysis. Predictive models of bilinear systems based on inductive knowledge extracted by big data mining techniques are applied with associative search of statistical patterns. A method and an algorithm for the elementwise solution of the generalized matrix Lyapunov equation are developed for discrete bilinear systems. The method is based on calculating the sequence of values of a fixed element of the solution matrix, which depends on the product of the eigenvalues of the dynamics matrix of the linear part and the elements of the nonlinearity matrixes. A sufficient condition for the convergence of all sequences is obtained, which is also a BIBO (bounded input bounded output) systems stability condition for the bilinear system.
Keywords: Gramian method; bilinear system process identification; generalized Lyapunov equation; knowledgebase; associative search models; wavelet analysis (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2021
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Citations: View citations in EconPapers (2)
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Persistent link: https://EconPapers.repec.org/RePEc:gam:jmathe:v:9:y:2021:i:24:p:3194-:d:699860
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