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主动队列管理中的PID型神经网络控制 被引量:2

PID Type Neural Network Control for Active Queue Management
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摘要 研究动态网络中间节点的拥塞控制.提出一种PID型神经网络的主动队列管理(AQM)算法,给出基于BP学习规则的网络参数自调整规律,根据Lyapunov定理证明了系统的稳定性.基于NS-2平台的仿真结果表明,该算法适应瞬息万变的网络环境,系统稳态误差和响应速度等指标优于PID算法. To study the congestion control of intermediate nodes in the changing network, PID type neural network control scheme for AQM (active queue management) is proposed. Back-propagation algorithm is used to adjust the weights of neural networks and stability of closed-loop system is proved according to the Lyapunov theory. Based on NS-2 simulation platform, the result showed that the proposed control scheme can adapt to the changing network situation, the system steady-state error and transient performance of the proposed scheme is superior to those of PID.
出处 《北京理工大学学报》 EI CAS CSCD 北大核心 2006年第10期892-896,共5页 Transactions of Beijing Institute of Technology
基金 国家自然科学基金资助项目(60474033)
关键词 主动队列管理(AQM) 拥塞控制 BP学习规则 active queue management congestion control back-propagation algorithm
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参考文献6

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二级参考文献21

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共引文献59

同被引文献24

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