Value of information in networked control systems subject to delay

TL;DR

This paper introduces a delay-sensitive Value-of-Information (VoI) metric for networked control systems, optimizing transmission decisions to improve control performance amid network delays and transmission costs.

Contribution

It develops a scalable VoI-based scheduling policy that outperforms existing methods by incorporating system parameters like delay and information freshness.

Findings

VoI-based policy outperforms periodic and AoI-based policies

The proposed VoI effectively balances transmission cost and control performance

Numerical simulations validate the approach under arbitrary network delays

Abstract

In this paper, we study the trade-off between the transmission cost and the control performance of the multi-loop networked control system subject to network-induced delay. Within the linear-quadratic-Gaussian (LQG) framework, the joint design of control policy and networking strategy is decomposed into separation optimization problems. Based on the trade-off analysis, a scalable, delay-dependent Value-of-Information (VoI) based scheduling policy is constructed to quantify the value of transmitting the data packet, and enables the decision-makers embedded in subsystems to determine the transmission policy. The proposed scalable VoI inherits the task criticality of the previous VoI metric meanwhile is sensitive to the system parameters such as information freshness and network delays. The VoI-based scheduling policy is proved to outperform the periodical triggering policy and existing Age-of-Information (AoI) based policy for network control system under transmission delay. The effectiveness of the constructed VoI with arbitrary network delay is validated through numerical simulations.