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Distributed optimized dynamic event-triggered control for unknown heterogeneous nonlinear MASs with

Lina Xia1, Qing Li2, Ruizhuo Song3

  • 1School of Automation and Electrical Engineering, University of Science and Technology Beijing, Beijing 100083, China; Key Laboratory of Knowledge Automation for Industrial Processes, Ministry of Education, Beijing, China; The Department of Electrical and Computer Engineering, National University of Singapore, 117576, Singapore.

Neural Networks : the Official Journal of the International Neural Network Society
|July 15, 2022
PubMed
Summary
This summary is machine-generated.

This study introduces a novel dynamic event-triggered controller for unknown nonlinear multi-agent systems (MASs). The controller efficiently manages communication and computation burdens while ensuring system synchronization.

Keywords:
Critic–actor NNsDynamic event-triggered controllerMIETUnknown heterogeneous nonlinear MASsZeno behavior

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Area of Science:

  • Control Theory
  • Artificial Intelligence
  • Robotics

Background:

  • Multi-agent systems (MASs) present challenges in control due to unknown dynamics and communication constraints.
  • Event-triggered control strategies aim to reduce communication load by only transmitting data when necessary.
  • Optimized control is crucial for efficient operation, especially under resource limitations.

Purpose of the Study:

  • To develop a distributed optimized dynamic event-triggered controller for unknown heterogeneous nonlinear MASs with input constraints.
  • To address communication and computing bottlenecks in MAS control.
  • To ensure robust synchronization and performance despite system uncertainties.

Main Methods:

  • Design of a distributed observer for leader information estimation.
  • Construction of an augmented system network incorporating follower and observer dynamics.
  • Development of an identifier with a compensator to approximate unknown system dynamics.
  • Leveraging a critic-actor-based optimized dynamic event-triggered controller with neural networks.
  • Proof of the existence of a positive minimum inter-event time (MIET).

Main Results:

  • An identifier with arbitrarily small error for unknown augmented systems.
  • A critic-actor-based controller that tunes parameters via a dynamic triggering mechanism.
  • A method for aperiodic sampling to maintain synchronization service.
  • Demonstration of a positive minimum inter-event time (MIET).

Conclusions:

  • The proposed controller effectively manages unknown nonlinear MASs under input constraints.
  • The dynamic event-triggered approach alleviates communication and computation burdens.
  • The method is validated through applications in non-identical nonlinear MAS and 2-DOF robots.