Aperiodically Intermittent Event-Triggered Optimal Average Consensus for Nonlinear Multi-Agent Systems

doi:10.1109/TNNLS.2023.3240427

Aperiodically Intermittent Event-Triggered Optimal Average Consensus for Nonlinear Multi-Agent Systems

2024-08-01

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DOI：10.1109/TNNLS.2023.3240427

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Abstract

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This article is concerned with average consensus of multi-agent systems via intermittent event-triggered strategy. First, a novel intermittent event-triggered condition is designed and the corresponding piecewise differential inequality for the condition is established. Using the established inequality, several criteria on average consensus are obtained. Second, the optimality has been investigated based on average consensus. The optimal intermittent event-triggered strategy in the sense of Nash equilibrium and corresponding local Hamilton-Jacobi-Bellman equation are derived. Third, the adaptive dynamic programming algorithm for the optimal strategy and its neural network implementation with actor-critic architecture are also given. Finally, two numerical examples are presented to show the feasibility and effectiveness of our strategies.

Keywords:

Optimal control

Laplace equations

Directed graphs

Eigenvalues and eigenfunctions

Consensus control

Topology

Nonlinear dynamical systems

Actor-critic architecture

aperiodically intermittent

average consensus

event-triggered mechanism

multi-agent systems (MASs)

optimal control

Aperiodically Intermittent Event-Triggered Optimal Average Consensus for Nonlinear Multi-Agent Systems

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