Comparison of MLP and RBF neural networks using deviation signals for indirect adaptive control of a synchronous generator

被引：5
|
作者：
Park, JW [1 ]
Harley, RG [1 ]
Venayagamoorthy, GK [1 ]
机构：
[1] Georgia Inst Technol, Sch Elect & Comp Engn, Atlanta, GA 30332 USA
来源：
PROCEEDING OF THE 2002 INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS, VOLS 1-3 | 2002年
关键词：
D O I：
10.1109/IJCNN.2002.1005597
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
This paper compares the performances of a multilayer perceptron neurocontroller (MLPNC) and a radial basis function neurocontroller (RBFNC) for backpropagation through time based indirect adaptive control of the synchronous generator. Also, the neurocontrollers are compared with the conventional controller for small as well as large disturbances to the power system.
引用
收藏
页码：919 / 924
页数：4
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