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Distributed Model-Free Bipartite Consensus Tracking for Unknown Heterogeneous Multi-Agent Systems with Switching

Huarong Zhao1, Li Peng1,2, Hongnian Yu3

  • 1Research Center of Engineering Applications for IOT, Jiangnan University, Wuxi 214122, China.

Sensors (Basel, Switzerland)
|July 31, 2020
PubMed
Summary
This summary is machine-generated.

This study introduces a model-free adaptive bipartite consensus tracking scheme for multi-agent systems. The method effectively tracks unknown trajectories in complex networks, ensuring reduced errors and robust performance.

Keywords:
bipartite consensusdata drivenmulti-agent systemswitching topologies

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Area of Science:

  • Control Theory
  • Robotics
  • Networked Systems

Background:

  • Multi-agent systems (MASs) often require coordinated behavior for complex tasks.
  • Achieving consensus in heterogeneous MASs with unknown dynamics and switching topologies is challenging.
  • Existing methods may rely on precise system models, limiting their applicability.

Purpose of the Study:

  • To develop a distributed model-free adaptive bipartite consensus tracking (DMFABCT) scheme.
  • To enable tracking of both time-invariant and time-varying trajectories in unknown discrete-time MASs.
  • To address systems with switching topologies and coopetition networks.

Main Methods:

  • Utilizing a pseudo partial derivative (PPD) approach to estimate an equivalent dynamic linearization data model.
  • Employing only input-output (I/O) data from each agent, eliminating the need for a precise mathematical model.
  • Investigating cooperative interactions within the multi-agent system.

Main Results:

  • The proposed DMFABCT scheme achieves bipartite consensus tracking for unknown dynamic discrete-time heterogeneous MASs.
  • The scheme demonstrates effectiveness and robustness even with switching topologies.
  • Rigorous proof confirms the convergent property, leading to reduced trajectory errors.

Conclusions:

  • The novel DMFABCT scheme offers a model-free solution for complex consensus tracking problems.
  • The approach is suitable for heterogeneous multi-agent systems with dynamic and topological uncertainties.
  • Simulations validate the effectiveness and robustness of the proposed DMFABCT scheme.