The identification of dynamic system based on memory RBF neural network

被引：0
|
作者：
Qiang, L [1 ]
Li, JX [1 ]
机构：
[1] Acad Armored Force Engn, Dept Control Engn, Beijing 100072, Peoples R China
来源：
ISTM/2005: 6th International Symposium on Test and Measurement, Vols 1-9, Conference Proceedings | 2005年
关键词：
RBF neural network; identification of dynamic system; recurrent neural network;
D O I：
暂无
中图分类号：
TH7 [仪器、仪表];
学科分类号：
0804 ; 080401 ; 081102 ;
摘要：
The memory RBF (MRBF) neural network (NN) is obtained by introducing memory neuron into the RBF neural network, and it functions a recurrent NN. The MRBF NN can identify dynamic system without feedbacking the past input and output, because the present output is related with the past input. Thus, the NN can identify the system of which the order or delay is unknown. In this paper, the learning algorithm is given and the correlative theory is proved. The simulation of dynamic system identification shows that method is valid, and can provide great potential for self-adaptive control.
引用
收藏
页码：1080 / 1083
页数：4
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