Fuzzy logic power system stabilizer based on genetically optimized adaptive network

被引：7
作者：
Hariri, A
Malik, OP
机构：
[1] SAGE Syst Div, Valmet Automat, Res & Technol Dept, Calgary, AB T2W 3X6, Canada
[2] Univ Calgary, Dept Elect & Comp Engn, Calgary, AB T2N 1N4, Canada
来源：
FUZZY SETS AND SYSTEMS | 1999年 / 102卷 / 01期
关键词：
fuzzy logic control; neural networks; genetic algorithms; power system stabilizer (PSS);
D O I：
10.1016/S0165-0114(98)00200-0
中图分类号：
TP301 [理论、方法];
学科分类号：
081202 ;
摘要：
An adaptive-network-based fuzzy logic power system stabilizer (PSS) is described here. A multi-layer adaptive network is used to design a fuzzy logic PSS with learning capability. Instead of using trial and error to find the number of inference rules, a genetic algorithm approach is employed to optimize the number of rules. Details of the design process are given and the effectiveness of the proposed stabilizer is demonstrated. (C) 1999 Elsevier Science B.V. All rights reserved.
引用
收藏
页码：31 / 40
页数：10
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