资源受限系统的灰色神经网络变采样调度算法

doi:10.16182/j.issn1004731x.joss.201804008

系统仿真学报 ›› 2018, Vol. 30 ›› Issue (4): 1272-1278.doi: 10.16182/j.issn1004731x.joss.201804008

资源受限系统的灰色神经网络变采样调度算法

时维国¹, 王力¹, 邵城²

1. 大连交通大学电气信息学院,辽宁大连 116028;
2. 大连理工大学控制科学与工程学院,辽宁大连 116024

收稿日期:2016-05-09 修回日期:2017-06-02 出版日期:2018-04-08 发布日期:2019-01-04
作者简介:时维国(1973-),男,河北,博士,副教授,研究方向为网络控制技术、智能控制;王力(1991-),女,河北,硕士生,研究方向为网络控制。
基金资助:
辽宁省自然科学基金(20170540141, 201602130)

Variable Sampling Period Scheduling Algorithm Based on Grey Neural Networks with Resource-constrained System

Shi Weiguo¹, Wang Li¹, Shao Cheng²

1. College of Electrical and Information, Dalian Jiaotong University, Dalian 116028, China;
2. School of Control and Science Engineering, Dalian University of Technology, Dalian 116024, China

Received:2016-05-09 Revised:2017-06-02 Online:2018-04-08 Published:2019-01-04

摘要/Abstract

摘要： 针对资源受限的网络控制系统,提出一种灰色RBF神经网络预测带宽的变采样周期调度算法。根据监测周期内历史和当前的网络带宽值,构造不同长度的原始时间序列,运用灰色预测方法得出不同的网络带宽预测数据,以灰色预测带宽数据作为RBF神经网络的输入,实现网络带宽的二次预测,确保网络带宽预测值能够真实反映网络的实际情况,以绝对误差积分参数为依据进行网络资源的动态分配,实时调整控制回路的采样周期。与固定采样周期EDF调度算法相比,仿真结果表明该灰色RBF神经网络预测的变采样周期调度算法具有更好的系统的控制性能及稳定性。

关键词: 灰色预测, RBF神经网络, 网络带宽, 变采样周期, 网络控制系统

Abstract: Considering networked control system of the limited resources, a kind of variable sampling period scheduling algorithm based on grey-RBF-neural-network prediction network bandwidth is proposed. According to the history and current network bandwidth values of monitoring period, the original time series of different lengths are built, and the grey prediction method is used to get different grey prediction data; the grey prediction data as the input of the RBF neural network are used to realize secondary prediction for network bandwidth, which ensures that prediction data can reflect the actual situation of the network; the absolute error integral parameter is used for the dynamic allocation of network resources, and this can adjust the sampling period of the control system in real-time. Compared with the fixed sampling period EDF scheduling algorithm, the simulation results show that the scheduling algorithm proposed has a better control performance and stability of the system.

Key words: grey prediction, RBF neural network, network bandwidth, variable sampling period, networked control system

中图分类号:

TP273

时维国, 王力, 邵城. 资源受限系统的灰色神经网络变采样调度算法[J]. 系统仿真学报, 2018, 30(4): 1272-1278.

Shi Weiguo, Wang Li, Shao Cheng. Variable Sampling Period Scheduling Algorithm Based on Grey Neural Networks with Resource-constrained System[J]. Journal of System Simulation, 2018, 30(4): 1272-1278.

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资源受限系统的灰色神经网络变采样调度算法

Variable Sampling Period Scheduling Algorithm Based on Grey Neural Networks with Resource-constrained System

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