Performance Optimization And Research Of Network Control System Based On Predictive Control

Networked Control Systems(NCS)is a closed-loop control system in which nodes such as controllers,actuators,and sensors are connected via a control network.While the network control system brings advantages and conveniences,the delay and packet loss in the process of network transmission have different degrees of influence on the system control performance.For the problem that the traditional control strategy is not ideal for application in the network control system,this paper studies how to use intelligent predictive control strategy to reduce the impact of network delay on the control system.First,this paper analyzes the causes of delay and packet loss in network control systems,and studies the effects of delay and packet loss on the performance of network control systems.This article uses Truetime 2.0 toolbox to build a DC motor network control system and conduct simulation experiments.Experiments show that the traditional control method can not effectively suppress the impact of network delay and packet loss on system performance.Second,for the problem of network delay,this paper designs a network control system optimization scheme based on neural network predictive control.In order to improve the prediction accuracy of neural network prediction model and the efficiency of rolling optimization control output,an adaptive mutation particle swarm optimization algorithm is proposed in this paper.The algorithm can selectively maintain the diversity and superiority of individuals by selectively mutating some particles,and ensure the global convergence and convergence speed of the algorithm.The adaptive mutation particle swarm optimization algorithm was applied to the BP neural network predictive modeling optimization and control signal rolling optimization of the predictive control system respectively.The simulation experiment results verify the effectiveness of the optimized scheme in the neural network predictive control system.Finally,in order to further reduce the impact of network delay and packet loss on the dynamic performance of the system,a delay compensation strategy is added to the predictive control system executor node.The results of simulation experiments under different network environments show that the neural network predictive control based on adaptive mutation particle swarm optimization can improve the dynamic response performance and stability of the system in thenetwork control system.The optimization design of the networked control system Have reference value.