Variable Sampling Approach to Mitigate Instability in Networked Control Systems With Delays

Abstract

This paper analyzes a new alternative approach to compensate for the effects of time delays on a dynamic networked control system (NCS). The approach is based on the use of time-delay-predicted values as the sampling times of the NCS. We use a one-step-ahead prediction algorithm based on an adaptive time delay neural network. The application of pole placement and linear quadratic regulator methods to compute the feedback gains taking into account the estimated time delays is investigated.

Data-Based Predictive Hybrid Driven Control for a Class of Imperfect Networked Systems

“…To address stability of NCSs with communication delays, many studies were carried out in which the controller designs were depended on assumptions that the time delay was constant [4], was bounded [2], [5]- [7], had a probability distribution function [8], or was represented based on time delay analyses [9], [10]. For NCSs with large delays, control concepts based on variable sampling periods using neural network or prediction theories were adopted [11]- [13]. Nevertheless, the observation of real delay data to train and construct the NCSs was not appropriately discussed.…”