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- W2373559466 abstract "Because of power systems being more and more complicated, besides low frequency oscillation by minus damp, there is also chaos oscillation that can not be dispelled by PSS in power systems. In order to early detect and suppress the chaos oscillation and improve power systems stability, a chaotic attractors space is reconstructed by the power system load time series, systemic embed dimension and maximal Lyapunov exponent are calculated in this paper. By above all, a chaos neural network model is constructed to detect and forecast chaos characters of the power systems even by the inputs including part outlier. If there is chaos oscillation in the power systems, a fuzzy-neural forecast controller is designed and forecast control is realized to the chaos oscillation. The validity of the project is proved by simulate results." @default.
- W2373559466 created "2016-06-24" @default.
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- W2373559466 date "2003-01-01" @default.
- W2373559466 modified "2023-09-28" @default.
- W2373559466 title "Chaos forecast and control of power systems based on chaos neural network model" @default.
- W2373559466 hasPublicationYear "2003" @default.
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