Semantics of Instability in Networked Control

TL;DR

This paper investigates optimal scheduling policies in cyber-physical systems with unreliable communication channels, aiming to balance system stability and resource constraints through a Markov decision process framework.

Contribution

It introduces a novel Markov decision process formulation for scheduling in networked control systems and derives an optimal multi-threshold policy for stability.

Findings

Derived an optimal multi-threshold scheduling policy.

Formulated the problem as a Markov decision process.

Achieved a balance between stability and resource use.

Abstract

This paper addresses a scheduling problem in the context of a cyber-physical system where a sensor and a controller communicate over an unreliable channel. The sensor observes the state of a source at each time, and according to a scheduling policy determines whether to transmit a compressed sampled state, transmit the uncompressed sampled state, or remain idle. Upon receiving the transmitted information, the controller executes a control action aimed at stabilizing the system, such that the effectiveness of stabilization depends on the quality of the received sensory information. Our primary objective is to derive an optimal scheduling policy that optimizes system performance subject to resource constraints, when the performance is measured by a dual-aspect metric penalizing both the frequency of transitioning to unstable states and the continuous duration of remaining in those states. We formulate this problem as a Markov decision process, and derive an optimal multi-threshold scheduling policy.