A Distributed Framework for Data-Driven Safe Coordination in Leader-Follower Networks

Fuente: arXiv
Enregistré dans:
Détails bibliographiques
Auteurs principaux: Urkmez, Mirhan, Sharifi, Maryam, Heshmati-Alamdari, Shahab
Format: Preprint
Publié: 2026
Sujets:
Accès en ligne:
Tags: Ajouter un tag
Pas de tags, Soyez le premier à ajouter un tag!
_version_ 1866911708094660608
author Urkmez, Mirhan
Sharifi, Maryam
Heshmati-Alamdari, Shahab
author_facet Urkmez, Mirhan
Sharifi, Maryam
Heshmati-Alamdari, Shahab
contents This paper addresses connectivity preservation in leader-follower multi-agent systems with unknown control-affine dynamics and local state information. We introduce the distributed data-driven zeroing control barrier function (3D-ZCBF) framework, which ensures the controlled invariance of safety sets by identifying derivative bounds from input-state data without requiring explicit models of high-dimensional agent dynamics. In this work, we derive the explicit, decoupled safety conditions necessary to maintain connectivity for leader-leader, and follower-follower pairings. These individual constraints, along with the leader-follower conditions, are aggregated into explicit system-wide conditions that formally guarantee the preservation of the entire communication network. Furthermore, we provide a quantitative analysis demonstrating how the size of the collected data set and the accuracy of the learned Jacobian bounds impact the feasibility of the safety certificates. The proposed conditions are implemented via a projection-based controller, and simulations confirm that these explicit 3D-ZCBF requirements effectively maintain system-level connectivity using only local, two-hop information.
format Preprint
id arxiv_https___arxiv_org_abs_2605_23356
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle A Distributed Framework for Data-Driven Safe Coordination in Leader-Follower Networks
Urkmez, Mirhan
Sharifi, Maryam
Heshmati-Alamdari, Shahab
Systems and Control
This paper addresses connectivity preservation in leader-follower multi-agent systems with unknown control-affine dynamics and local state information. We introduce the distributed data-driven zeroing control barrier function (3D-ZCBF) framework, which ensures the controlled invariance of safety sets by identifying derivative bounds from input-state data without requiring explicit models of high-dimensional agent dynamics. In this work, we derive the explicit, decoupled safety conditions necessary to maintain connectivity for leader-leader, and follower-follower pairings. These individual constraints, along with the leader-follower conditions, are aggregated into explicit system-wide conditions that formally guarantee the preservation of the entire communication network. Furthermore, we provide a quantitative analysis demonstrating how the size of the collected data set and the accuracy of the learned Jacobian bounds impact the feasibility of the safety certificates. The proposed conditions are implemented via a projection-based controller, and simulations confirm that these explicit 3D-ZCBF requirements effectively maintain system-level connectivity using only local, two-hop information.
title A Distributed Framework for Data-Driven Safe Coordination in Leader-Follower Networks
topic Systems and Control
url https://arxiv.org/abs/2605.23356