A Leader–Follower Attack-Tolerant Algorithm for Resilient Rendezvous With Reduced Network Redundancy

This article addresses the resilient rendezvous problem for leader–follower multiagent systems (MASs) in the presence of adversarial attacks. A novel leader–follower attack-tolerant (LFAT) algorithm is developed to ensure that the healthy followers reach rendezvous on the reference value propagated by healthy leaders. Compared with the existing weighted mean-subsequence-reduced algorithm, the proposed LFAT algorithm includes a necessary state initialization step for leader and follower agents and an improved threat elimination step, so that more effective information can be retained for state updates. The necessary and sufficient condition on the network topology is further derived to ensure resilient rendezvous for leader–follower MASs. Compared with the existing resilient algorithms, the proposed LFAT algorithm enables MASs to achieve leader–follower resilient rendezvous under relaxed graph robustness conditions, so that the network redundancy is mitigated. Several numerical examples are given to illustrate the superior performance of the LFAT algorithm and the scalability to larger-scale and time-varying networks.

Authors

Institutions

Publication Details

Journal
IEEE Systems Journal
Published
2025-01-10
DOI
https://doi.org/10.1109/jsyst.2024.3523485
Citations
8
Primary Topic
Distributed Control Multi-Agent Systems
Type
article
Field-Weighted Citation Impact
11.90

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

A Leader–Follower Attack-Tolerant Algorithm for Resilient Rendezvous With Reduced Network Redundancy

Shaoping Wang, Zirui Liao, Yuwei Zhang, Jian Shi et al.
8 citations
IEEE Systems Journal
Distributed Control Multi-Agent Systems
11.90
article

A Leader–Follower Attack-Tolerant Algorithm for Resilient Rendezvous With Reduced Network Redundancy

Shaoping Wang, Zirui Liao, Yuwei Zhang, Jian Shi, Zhiyong Sun, Rentong Chen
article en
8 citations

Abstract

This article addresses the resilient rendezvous problem for leader–follower multiagent systems (MASs) in the presence of adversarial attacks. A novel leader–follower attack-tolerant (LFAT) algorithm is developed to ensure that the healthy followers reach rendezvous on the reference value propagated by healthy leaders. Compared with the existing weighted mean-subsequence-reduced algorithm, the proposed LFAT algorithm includes a necessary state initialization step for leader and follower agents and an improved threat elimination step, so that more effective information can be retained for state updates. The necessary and sufficient condition on the network topology is further derived to ensure resilient rendezvous for leader–follower MASs. Compared with the existing resilient algorithms, the proposed LFAT algorithm enables MASs to achieve leader–follower resilient rendezvous under relaxed graph robustness conditions, so that the network redundancy is mitigated. Several numerical examples are given to illustrate the superior performance of the LFAT algorithm and the scalability to larger-scale and time-varying networks.

IEEE Systems JournalVol. 19(1)
University of Nottingham Ningbo China (CN), Peking University (CN), State Key Laboratory of Turbulence and Complex Systems, Beihang University (CN)
National Natural Science Foundation of China
Climate action
Openalex Percentile: Top 2%
Distributed Control Multi-Agent Systems
11.90
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

A Leader–Follower Attack-Tolerant Algorithm for Resilient Rendezvous With Reduced Network Redundancy — Shaoping Wang, Zirui Liao, et al. · IEEE Systems Journal (2025) | TGRS Research Map | TGRS