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

Authors

Weiguo Shi, 1. College of Electrical and Information, Dalian Jiaotong University, Dalian 116028, China; ;
Wang Li, 1. College of Electrical and Information, Dalian Jiaotong University, Dalian 116028, China; ;
Shao Cheng, 2. School of Control and Science Engineering, Dalian University of Technology, Dalian 116024, China;

Abstract

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.

Recommended Citation

Shi, Weiguo; Li, Wang; and Cheng, Shao (2019) "Variable Sampling Period Scheduling Algorithm Based on Grey Neural Networks with Resource-constrained System," Journal of System Simulation: Vol. 30: Iss. 4, Article 8.
DOI: 10.16182/j.issn1004731x.joss.201804008
Available at: https://dc-china-simulation.researchcommons.org/journal/vol30/iss4/8

First Page

1272

Revised Date

2017-06-02

DOI Link

https://doi.org/10.16182/j.issn1004731x.joss.201804008

Last Page

1278

CLC

TP273

Recommended Citation

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.

DOI

10.16182/j.issn1004731x.joss.201804008