Active Queue Management Algorithm Based on RBF Neural Network Controller

被引：0

作者：

Zhang, Wenli ^{[1
]}

Jing, Yuanwei ^{[1
]}

机构：

[1] Northeastern Univ, Coll Informat Sci & Engn, Shenyang 110819, Peoples R China

来源：

PROCEEDINGS OF THE 32ND 2020 CHINESE CONTROL AND DECISION CONFERENCE (CCDC 2020) | 2020年

关键词：

TCP Network System; Network Congestion Control; Active Queue Management; RBF neural network; Neural network controller;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Considering the problem of input saturation and UDP flows, the TCP nonlinear dynamic model is improved. On account of the nonlinearity, uncertainty and time-variability of the improved model, the nonlinear RBF neural network controller is designed by using the neural network control strategy. In simulation experiments, the effectiveness and anti-interference of the active queue management algorithm based on RBF neural network controller are verified and the controller's superiority is shown in the comparison simulation with the active queue management algorithm based on PID controller.

引用

页码：2289 / 2293

页数：5

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