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Prescribed-time cluster practical consensus for nonlinear multi-agent systems based on event-triggered mechanism.

Wangming Lu1, Zhiyong Yu1, Zhanheng Chen2

  • 1College of Mathematics and System Sciences, Xinjiang University, Urumqi 830017, China.

Mathematical Biosciences and Engineering : MBE
|March 29, 2024
PubMed
Summary
This summary is machine-generated.

This study achieves prescribed-time cluster practical consensus in nonlinear multi-agent systems using a novel algorithm and virtual leaders. Event-triggered protocols prevent overlapping states and Zeno behavior, ensuring efficient coordination.

Keywords:
cluster consensusevent-triggeredmulti-agent systemsprescribed-time

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Area of Science:

  • Control Theory
  • Multi-Agent Systems
  • Nonlinear Systems

Background:

  • Coordinated control of nonlinear multi-agent systems is challenging due to external disturbances.
  • Achieving consensus within a specified time frame (prescribed-time) adds complexity.
  • Cluster consensus requires agents to form groups with distinct final states.

Purpose of the Study:

  • To develop a distributed algorithm for achieving prescribed-time cluster practical consensus in nonlinear multi-agent systems.
  • To design an event-triggered control protocol to reduce communication load.
  • To ensure that distinct clusters do not have overlapping final states and to avoid Zeno behavior.

Main Methods:

  • Introduction of a novel time-varying function and a distributed continuous algorithm.
  • Application of Lyapunov stability theory and inequality techniques to derive consensus conditions.
  • Inclusion of virtual leaders for each cluster to manage state separation.
  • Development of an event-triggered distributed protocol.

Main Results:

  • Sufficient conditions are established for achieving prescribed-time cluster practical consensus.
  • The proposed event-triggered protocol effectively manages cluster coordination.
  • Virtual leaders prevent overlapping final states between clusters.
  • Zeno behavior is proven to be avoidable through appropriate parameter selection.

Conclusions:

  • The developed methods ensure prescribed-time cluster practical consensus for nonlinear multi-agent systems under disturbances.
  • The event-triggered approach offers an efficient communication strategy.
  • The theoretical results are validated through numerical examples, demonstrating practical applicability.