Stability of discrete-time plants using model-based control with intermittent feedback

In this paper we study the stability of discrete-time plants in a networked control setting, employing an approach known as model-based networked control systems (MB-NCS) with Intermittent Feedback. Model-Based Networked Control Systems use an explicit model of the plant in order to reduce the network traffic while attempting to prevent excessive performance degradation, while Intermittent Feedback consists of the loop remaining closed for some fixed interval, then open for another interval. We provide a full description of the output, as well as a necessary and sufficient condition for stability of the system. We also extend our results to the case where the full state of the plant is not known, so that we resort to a state observer. Finally, we investigate the situation where the update times are time-varying, first addressing the case where they have upper and lower bounds, then moving on to the case where their distributions are i.i.d or driven by a Markov chain.