Online Multi-step Prediction for the Random Delay of the Forward Channel in Networked Control System

To address uncertainty caused by random delay of the forward channel in a networked control system, we propose an online predictive model based on an autoregressive (AR) model on account of timing analysis. We use the TrueTime toolbox to establish the simulation system in which the delay series is collected through the feedback channel. After pretreatment, we establish the AR model with the delay series, and the parameters are updated online by using a recursive least-squares algorithm. A rolling forecast is considered to realize multi-step prediction for the delay of the forward channel. Experimental results suggest that this online predictive model has better predictive performance than the GRNN-based model.