Collaborative Safety-Critical Control for Dynamically Coupled Networked Systems

TL;DR

This paper introduces a decentralized control method using collaborative control barrier functions to ensure safety in complex, interconnected networked systems, with proven convergence guarantees and application to epidemic models.

Contribution

It proposes a novel collaborative control barrier function framework and a decentralized algorithm for safe control of networked agents with convergence guarantees.

Findings

Algorithm guarantees convergence to safe control actions

Framework applicable to epidemic network models

Conditions for forward invariance of safety sets

Abstract

As modern systems become ever more connected with complex dynamic coupling relationships, developing safe control methods becomes paramount. In this paper, we discuss the relationship of node-level safety definitions for individual agents with local neighborhood dynamics. We define a collaborative control barrier function (CCBF) and provide conditions under which sets defined by these functions will be forward invariant. We use collaborative node-level control barrier functions to construct a novel \edit{decentralized} algorithm for the safe control of collaborating network agents and provide conditions under which the algorithm is guaranteed to converge to a viable set of safe control actions for all agents. We illustrate these results on a networked susceptible-infected-susceptible (SIS) model.