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Event-triggered containment control for second-order multi-agent systems with sampled position data.

Hong Xia1, Wei Xing Zheng2, Jinliang Shao3

  • 1School of Mathematical Sciences, University of Electronic Science and Technology of China, Chengdu, Sichuan 611731, PR China; School of Computing, Engineering and Mathematics, Western Sydney University, Sydney, NSW 2751, Australia.

ISA Transactions
|December 16, 2017
PubMed
Summary
This summary is machine-generated.

This study introduces an event-triggered containment control protocol for multi-agent systems using sampled data. It ensures agents remain within a defined boundary, optimizing control strategies.

Keywords:
Containment controlEvent-triggeredMulti-agent systemsSampled position data

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Area of Science:

  • Control Theory
  • Multi-Agent Systems
  • Robotics

Background:

  • Multi-agent systems require coordinated control for complex tasks.
  • Event-triggered control reduces communication load compared to time-triggered systems.
  • Containment control aims to confine agents within a specific region.

Purpose of the Study:

  • To develop an event-triggered containment control protocol for second-order multi-agent systems.
  • To utilize only sampled position data for control and event-triggering.
  • To establish conditions for achieving containment control under intermittent examination of the triggering condition.

Main Methods:

  • Design of a distributed event-triggered containment control protocol.
  • Utilization of sampled position data and constant sampling instants.
  • Application of algebraic graph theory and matrix theory.

Main Results:

  • A sufficient condition for achieving containment control was derived.
  • The condition depends on communication topology, controller gains, and sampling period.
  • Theoretical results were validated through a numerical example.

Conclusions:

  • The proposed event-triggered protocol effectively achieves containment control for second-order multi-agent systems.
  • The derived conditions provide guidelines for designing such control systems.
  • The approach offers a communication-efficient method for coordinated agent behavior.