Emergent Dynamics of an Orientation Flocking Model With Distance‐Dependent Delay

ABSTRACT In this paper, we investigate the dynamical behaviors of an orientation flocking model that incorporates state‐dependent delay. The research unfolds in three principal phases: First, we establish the global existence and uniqueness of solutions for our system. Subsequently, we develop a comprehensive theoretical framework that provides sufficient conditions for the emergence of orientation flocking phenomena. In particular, this framework remains valid regardless of the number of particles . In the final phase of our analysis, we perform a systematic derivation of the mean‐field limit for the discrete system, accompanied by a proof of global well‐posedness for the resulting mean‐field equations. Furthermore, we demonstrate that our theoretical results and analytical framework naturally extend to and encompass the case of orientation flocking models with constant time delays.

Authors

Institutions

Publication Details

Journal
Mathematical Methods in the Applied Sciences
Published
2025-05-04
DOI
https://doi.org/10.1002/mma.11031
Primary Topic
Distributed Control Multi-Agent Systems
Type
article
Field-Weighted Citation Impact
0.00

Funders

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

Emergent Dynamics of an Orientation Flocking Model With Distance‐Dependent Delay

Zhengyang Qiao, Xiao Wang, Maoli Chen, Yicheng Liu
Mathematical Methods in the Applied Sciences
Distributed Control Multi-Agent Systems
article

Emergent Dynamics of an Orientation Flocking Model With Distance‐Dependent Delay

Zhengyang Qiao, Xiao Wang, Maoli Chen, Yicheng Liu
article en

Abstract

ABSTRACT In this paper, we investigate the dynamical behaviors of an orientation flocking model that incorporates state‐dependent delay. The research unfolds in three principal phases: First, we establish the global existence and uniqueness of solutions for our system. Subsequently, we develop a comprehensive theoretical framework that provides sufficient conditions for the emergence of orientation flocking phenomena. In particular, this framework remains valid regardless of the number of particles . In the final phase of our analysis, we perform a systematic derivation of the mean‐field limit for the discrete system, accompanied by a proof of global well‐posedness for the resulting mean‐field equations. Furthermore, we demonstrate that our theoretical results and analytical framework naturally extend to and encompass the case of orientation flocking models with constant time delays.

Mathematical Methods in the Applied SciencesVol. 48(12)
National University of Defense Technology (CN), Beijing Electronic Science and Technology Institute (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 91%
Distributed Control Multi-Agent Systems
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.