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Tracking Consensus for Nonlinear Multi-Agent Systems Under Asynchronous Switching and Undirected Topology.

Shanyan Hu1, Mengling Wang1,2

  • 1Key Laboratory of Smart Manufacturing in Energy Chemical Process, Ministry of Education, East China University of Science and Technology, Shanghai 200237, China.

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|August 14, 2025
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Summary
This summary is machine-generated.

This study addresses nonlinear multi-agent tracking consensus with asynchronous delays using an event-triggered mechanism (ETM). It establishes stability conditions and designs controllers via Linear Matrix Inequalities (LMIs) for improved efficiency.

Keywords:
asynchronous switchingdynamic event-triggered mechanismmulti-agent systemstracking consensus

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Area of Science:

  • Control Systems Engineering
  • Networked Systems Theory
  • Nonlinear Dynamics

Background:

  • Achieving consensus in multi-agent systems is crucial for coordinated behavior.
  • Asynchronous switching and delays in communication topology complicate control design.
  • Event-triggered mechanisms (ETMs) are vital for reducing communication and computational load.

Purpose of the Study:

  • To investigate tracking consensus in nonlinear multi-agent systems with undirected topology.
  • To address challenges posed by asynchronous delays between topology and controller switching.
  • To develop an efficient control strategy using an event-triggered mechanism.

Main Methods:

  • Utilizing properties of undirected topology graphs to simplify controller design.
  • Dividing system operation into synchronized and delayed modes to handle asynchronous delays.
  • Constructing an augmented Lyapunov function to establish system stability conditions.
  • Employing an event-triggered mechanism (ETM) to minimize controller updates.
  • Solving Linear Matrix Inequalities (LMIs) to derive the dynamic ETM-based controller.

Main Results:

  • Sufficient conditions for ensuring system stability under asynchronous switching are established.
  • A dynamic event-triggered controller is designed, reducing communication and computation.
  • The proposed method effectively achieves tracking consensus in nonlinear multi-agent systems.
  • Simulation results validate the effectiveness of the developed control strategy.

Conclusions:

  • The developed approach effectively handles asynchronous delays in nonlinear multi-agent systems.
  • The event-triggered mechanism significantly enhances control efficiency.
  • The controller design based on LMIs ensures system stability and tracking consensus.