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Active Queue Management Algorithm Based on RBF Neural Network Controller

机译:基于RBF神经网络控制器的主动队列管理算法

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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.
机译:考虑到输入饱和度和UDP流量的问题,改进了TCP非线性动态模型。针对改进模型的非线性,不确定性和时变性,采用神经网络控制策略设计了非线性RBF神经网络控制器。在仿真实验中,验证了基于RBF神经网络控制器的主动队列管理算法的有效性和抗干扰性,并与基于PID控制器的主动队列管理算法进行了比较仿真,显示了该控制器的优越性。

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