基于小波神经网络的工业以太网延时预测控制  

Delay prediction control for industrial ethernet based on wavelet neural network

作　　者：刘达[1,2] 李木国[1] 杜海[1] 

机构地区：[1]大连理工大学海岸和近海工程国家重点实验室,辽宁大连116024 [2]大连海事大学信息科学技术学院,辽宁大连116026

出　　处：《大连理工大学学报》2014年第2期246-250,共5页Journal of Dalian University of Technology

基　　金：国家自然科学基金资助项目(61202253)

摘　　要：随着网络控制研究的兴起,对工业以太网延时进行补偿成为研究的重点方向.针对网络延时给网络控制系统带来的问题,提出用小波神经网络对工业以太网延时进行预测,根据输入的过去时间延迟序列预测输出下一采样时刻的网络延时值.预测模型的参数通过训练算法实时更新,以保证预测输出的准确性.对实际工业以太网延时数据样本的预测分析表明,该预测模型能够有效预测延时.为进一步说明延时预测效果,将延时预测模型应用于网络控制系统进行延时的预测与补偿,系统仿真结果证明了预测模型预测的准确性及补偿的有效性.As the rising of network control study,industrial ethernet delay compensation has become an important research direction.In order to solve problems caused by network delay in network control system,an algorithm is proposed to predict industrial ethernet delay using wavelet neural network.The controller applying this algorithm can output the predicted time delay value of the next sampling by processing inputted past delay sequence,and the prediction model parameters are updated in real time through the training algorithm to ensure the accuracy of the prediction output. Experiments using the real delay data of industrial ethernet are carried out to test the performance of the algorithm.The experimental results indicate that the prediction model can predict the delay effectively.To further verify the effectiveness of delay prediction,simulation experiments have been operated in which the delay prediction model has been applied to the network control system for delay prediction and compensation.The simulation results demonstrate the prediction accuracy of prediction model and the effectiveness of compensation.

关 键 词：工业以太网 网络延时预测 延时补偿 小波神经网络 

分 类 号：TP273.5[自动化与计算机技术—检测技术与自动化装置]