Consensus of a Class of Nonlinear Systems With Varying Topology: A Hilbert Metric Approach

In this technical note, we introduce a novel approach to studying consensus of continuous-time nonlinear systems with varying topology based on Hilbert metric. We demonstrate that this metric offers significant flexibility in analyzing consensus properties, while effectively handling nonlinearities and time dependencies. Notably, our approach relaxes key technical assumptions from some standard results while yielding stronger conclusions with shorter proofs. This framework provides new insights into nonlinear consensus under varying topology.

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Publication Details

Journal
IEEE Transactions on Automatic Control
Published
2025-05-14
DOI
https://doi.org/10.1109/tac.2025.3570225
Primary Topic
Advanced Differential Equations and Dynamical Systems
Type
article
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article

Consensus of a Class of Nonlinear Systems With Varying Topology: A Hilbert Metric Approach

Dongjun Wu
IEEE Transactions on Automatic Control
Advanced Differential Equations and Dynamical Systems
article

Consensus of a Class of Nonlinear Systems With Varying Topology: A Hilbert Metric Approach

Dongjun Wu
article en

Abstract

In this technical note, we introduce a novel approach to studying consensus of continuous-time nonlinear systems with varying topology based on Hilbert metric. We demonstrate that this metric offers significant flexibility in analyzing consensus properties, while effectively handling nonlinearities and time dependencies. Notably, our approach relaxes key technical assumptions from some standard results while yielding stronger conclusions with shorter proofs. This framework provides new insights into nonlinear consensus under varying topology.

IEEE Transactions on Automatic ControlVol. 70(11)
Lund University (SE)
Reduced inequalities
Openalex Percentile: Top 85%
Advanced Differential Equations and Dynamical Systems
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Consensus of a Class of Nonlinear Systems With Varying Topology: A Hilbert Metric Approach — Dongjun Wu · IEEE Transactions on Automatic Control (2025) | TGRS Research Map | TGRS