Multi-machine fuzzy logic excitation and governor stabilizers design using genetic algorithms

F. Mayouf, F. Djahli, A. Mayouf, T. Devers
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引用次数: 2

Abstract

In this paper, we have extended to the multimachine case our developed control model for SMIB stability improvement previously published. This model implements the fuzzy stabilizer in excitation and/or in turbine Governor systems (FLCE, FLCG and FLCEG). The optimal adjustment of the fuzzy logic controllers using genetic algorithm is carried out. Results obtained by nonlinear simulation using Matlab/Simulink of a multimachine system show the effectiveness of using both fuzzy controllers to exciter (FLCE) and to governor (FLCG) at the same time (FLCEG) for large and small disturbances.
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用遗传算法设计多机模糊逻辑激励和调速器稳定器
在本文中,我们将先前发表的SMIB稳定性改进控制模型扩展到多机情况。该模型在励磁和/或汽轮机调节系统(FLCE、FLCG和FLCEG)中实现模糊稳定器。采用遗传算法对模糊控制器进行最优调整。利用Matlab/Simulink对多机系统进行了非线性仿真,结果表明,对于大小扰动,模糊控制器同时用于激励器(FLCE)和调节器(FLCG)是有效的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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