Communication, Sensing and Control integrated Closed-loop System: Modeling, Control Design and Resource Allocation

TL;DR

This paper develops an integrated model for wireless communication, sensing, and control in industrial systems, addressing their interdependencies and proposing a joint optimization approach for system performance enhancement.

Contribution

It introduces a unified closed-loop model that captures the coupling effects between uplink and downlink communications and proposes a joint control and resource allocation algorithm.

Findings

Derived an inequality linking sensing, communication, and control performances.

Proposed a joint optimization algorithm for control and resource allocation.

Simulation results demonstrate the impact of system parameters on performance.

Abstract

The wireless communication technologies have fundamentally revolutionized industrial operations. The operation of the automated equipment is conducted in a closed-loop manner, where the status of devices is collected and sent to the control center through the uplink channel, and the control center sends the calculated control commands back to the devices via downlink communication. However, existing studies neglect the interdependent relationship between uplink and downlink communications, and there is an absence of a unified approach to model the communication, sensing, and control within the loop. This can lead to inaccurate performance assessments, ultimately hindering the ability to provide guidance for the design of practical systems. Therefore, this paper introduces an integrated closed-loop model that encompasses sensing, communication, and control functionalities, while addressing the coupling effects between uplink and downlink communications. Through the analysis of system convergence, an inequality pertaining to the performances of sensing, communication, and control is derived. Additionally, a joint optimization algorithm for control and resource allocation is proposed. Simulation results are presented to offer an intuitive understanding of the impact of system parameters. The findings of this paper unveil the intricate correlation among sensing, communication, and control, providing insights for the optimal design of industrial closed-loop systems.