Title: A novel method for time delay prediction in networked control systems

Authors: Pei Xu; Jianguo Wu

Addresses: School of Computer Science and Technology, Anhui University, Hefei 230601, China ' School of Computer Science and Technology, Anhui University, Hefei 230601, China

Abstract: Time delay prediction is a crucial issue of networked control systems. Previous methods mainly use individual model to predict time delay, which causes the limitation that the proposed model can only be suitable applied to either linear or nonlinear data. This paper proposed a novel method to predict time delay in networked control systems which considers several different individual models as the component models to form a combined model and takes full advantages of these component models. By applying Lagrange multiplier method to minimise prediction error, the proposed optimal weight (OW) algorithm is able to calculate the proper weight coefficients of component models in order to improve the prediction performance. Compared with the existing methods, the proposed combined model can improve the prediction accuracy and support robustness, variability and scalability. The simulation experiments verify the effectiveness of the proposed method.

Keywords: networked control systems; time delay prediction; RBF neural network; ARMA model; optimal weight; OW; combined model.

DOI: 10.1504/IJAHUC.2019.102454

International Journal of Ad Hoc and Ubiquitous Computing, 2019 Vol.32 No.2, pp.99 - 109

Received: 19 Mar 2018
Accepted: 30 Apr 2018
Published online: 26 Sep 2019 *

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