Mathematical model of mobile network reliability control based on nonlinear proportional differential

In order to improve the reliability of mobile network, a mathematical model of mobile network reliability control based on nonlinear PDE is proposed. Fuzzy Smith neural network structure is used to construct the controlled object model of mobile network reliability control, and the time-varying delay function of mobile network control is constructed by non-linear proportional differential equation under the condition of bounded delay. The convergence constraint function of mobile network control is combined with Lyapunov function, and the fuzzy adaptive learning is carried out according to the weight of network output. A time-delay hyperbolic proportional differential control feedback unit for hidden layer weight learning of mobile network is constructed. Robustness training of reliability output of mobile network is carried out in the boundary value control node. The singular eigenvalues of the control output of mobile network are extracted, and the convergence is judged in the solution space of the singular value distribution. The optimal solution of the network output is obtained according to the learning method of LM-Smith neural network. A non-linear Jacobian matrix is constructed to analyze the stability of the mathematical model of the reliability control of mobile network. The simulation results show that this method has good reliability and fine steady-state convergence for mobile network output control, which reduces the output error of the mobile network.