A probabilistic scheduling algorithm for networked control systems

TL;DR

This paper introduces a probabilistic scheduling algorithm for networked control systems with limited communication capacity, ensuring stochastic stability through a Markovian jump linear system framework and static controllers.

Contribution

It proposes a novel probabilistic scheduling method and static controller design to guarantee stability in networked control systems with capacity constraints.

Findings

The scheduling algorithm ensures stochastic stability under certain conditions.

Stability conditions are expressed via matrix inequalities.

Numerical experiments validate the approach.

Abstract

This paper deals with the design of scheduling logics for Networked Control Systems (NCSs) whose communication networks have limited capacity. We assume that only a subset of the plants can communicate with their controllers at any time instant. Our contributions are twofold. First, we present a probabilistic algorithm to design scheduling logics that, under certain conditions on the plant and controller dynamics and the capacity of the network, ensure stochastic stability of each plant in an NCS. Second, given the plant dynamics and the capacity of the network, we design static state-feedback controllers such that the conditions for stability under our scheduling logics are satisfied. The main apparatus for our analysis is a Markovian jump linear system representation of the individual plants in an NCS. Our stability conditions involve sets of matrix inequalities. We present numerical experiments to demonstrate our results.