A Method to Predict Random Time-Delay of Networked Control System

Abstract

The time-delay in a networked control system is difficult to predict accurately. In order to improve prediction performance, a time-delay prediction method is proposed. Firstly, the approximation components with low-frequency and approximation components with a high frequency of time-delay sequence are obtained through the decomposition and reconstruction of Db3 (Daubechies 3) wavelet transform. Secondly, the characteristics of the approximate component and detail components are analyzed. Fractal autoregressive integrated moving average (FARIMA) is chosen as the prediction model for an approximate component. Autoregressive integrated moving average (ARIMA) is chosen as the prediction model for detail components. Finally, the final prediction value can be obtained by the prediction value of FARIMA adding the prediction value of ARIMA. The proposed prediction method combines the advantages of FARIMA and ARIMA. The case study results show that the proposed prediction method has better prediction accuracy.

KEYWORDS:

• Networked control system
• Wavelet transform
• Fractal autoregressive integrated moving average
• Autoregressive integrated moving average
• Time-delay prediction

ACKNOWLEDGEMENT

This work is partially supported by Science Research Project of Liaoning Education Department under grant LGD2016009.

Additional information

Funding

This work is partially supported by Scientific Research Fund of Liaoning Provincial Education Department under grant LGD2016009.

Notes on contributors

Zhongda Tian

Zhongda Tian received the PhD degree in control theory and control engineering from Northeastern University, China in 2013. He is currently an associate professor in College of Information Science and Engineering, Shenyang University of Technology, China. His research interests include predictive control, delay compensation and scheduling for networked control system, time series prediction. Email: [email protected]