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Updated: Jan 23, 2026

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Positive edge consensus of networked systems with input saturation.

Han Wu1, Housheng Su2

  • 1School of Artificial Intelligence and Automation, Image Processing and Intelligent Control Key Laboratory of Education Ministry of China, Huazhong University of Science and Technology, Luoyu Road 1037, Wuhan 430074, China; School of Information Science and Engineering, Wuhan University of Science and Technology, 947 Heping Avenue, Qingshan District, Wuhan, Hubei 430081, China.

ISA Transactions
|June 23, 2019
PubMed
Summary

This study addresses edge consensus in networked systems with input saturation, achieving global consensus without needing full network topology. The findings are verified through simulations.

Keywords:
Edge consensusGlobal consensusInput saturationPositivity constraintUncertain parameters

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Area of Science:

  • Control Theory
  • Networked Systems
  • Systems Engineering

Background:

  • Networked systems often face challenges like input saturation and positivity constraints.
  • Edge consensus problems are crucial for distributed system coordination.

Purpose of the Study:

  • To investigate edge consensus problems in undirected networked systems with positivity constraints and input saturation.
  • To develop conditions for global positive edge consensus using limited topology information.

Main Methods:

  • Introduction of an edge network definition and analysis of edge dynamics under input saturation.
  • Derivation of bounds for nonzero eigenvalues of the edge Laplacian matrix.
  • Application of positive system properties and Metzler matrix characteristics for convergence analysis.

Main Results:

  • Sufficient conditions for positive edge consensus with input saturation are established, independent of global topology.
  • The study achieves global consensus, surpassing semi-global consensus in related works.
  • A feedback matrix calculable via linear matrix inequality is presented.

Conclusions:

  • The proposed methods ensure global positive edge consensus even with input saturation and uncertain parameters.
  • The results offer a robust approach to consensus problems in networked systems.
  • Numerical and practical simulations confirm the efficacy of the developed methods.