主动队列管理中的PID型神经网络控制

PID Type Neural Network Control for Active Queue Management

  • 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.

     

    Abstract: 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.

     

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