Adjustable Sampling Rate – An Efficient Way to Reduce the Impact of Network-Induced Uncertainty in Networked Control Systems?

Abstract

The practical realization of Network Control Systems (NCSs) enforces handling network-induced effects: information transfer and processing delay, delay variability, packet loss and reordering, etc. The impact of these phenomena can be limited by using dedicated, expensive real-time networks and control systems, or by implementation of algorithmic methods. This paper presents an adjustable sampling rate (ASR) algorithm to alleviate negative influence of network-induced uncertainty in NCSs, and compares it with previously developed predictor based (PB) one in a common experimental framework. Since the experiments are conducted using standard modules and communication technologies, the reported results are applicable to a relatively broad class of remote control applications and NCSs.