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- W2005632012 abstract "This paper presents an adaptive neuro-fuzzy technique based on Sugeno first-order fuzzy model for tuning the parameters of a conventional phase lead-lag PSS from on online measurements of the generator loading conditions using adaptive neuro-fuzzy inference system (ANFIS) architecture. Input patterns, of the proposed ANFIS, comprising the generator real power Pe and reactive power Qe are associated with the corresponding output patterns of the desired PSS parameters Kc and T1(T3) over a wide range of operating conditions. Once trained the proposed ANFIS-PSS is capable of providing the PSS parameters Kc and T1 in real time for any generator loading conditions. Simulation results under small disturbances at different loading conditions have been carried out to assess the effectiveness and robustness of the proposed ANF-PSS in enhancing enhance the small signal stability of the power system." @default.
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- W2005632012 date "2006-09-01" @default.
- W2005632012 modified "2023-09-27" @default.
- W2005632012 title "Adaptive Neuro-Fuzzy Technique for Tuning Power System Stabilizer" @default.
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- W2005632012 doi "https://doi.org/10.1109/upec.2006.367737" @default.
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