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Periodic event-triggered impulsive control for fully heterogeneous stochastic multi-agent systems with a time-varying topology

Xuetao Yang, Ruilu An, Quanxin Zhu

TL;DR

This work addresses consensus in fully heterogeneous stochastic multi-agent systems with a time-varying topology by introducing a virtual state space to equalize agent dimensions and an energy-adaptive topology to modulate information flow. It develops periodic event-triggered impulsive controls (PETIC) with and without actuation delays, proving mean-square exponential convergence under specific conditions. The approach substantially reduces communication load while maintaining stability, demonstrated via UAV/UGV simulations with stochastic disturbances. Overall, the paper advances practical coordination for heterogeneous agents in energy-constrained, dynamic environments by combining topology adaptation, virtual-state reasoning, and PETIC to achieve robust consensus.

Abstract

In this paper, we focus on a periodic event-triggered impulsive control (PETIC) for fully heterogeneous stochastic multi-agent systems (MASs) with a time-varying topology. Firstly, a novel time-varying topology is established by incorporating the energy consumption of each agent. This topology enables active adjustment of the information interaction intensity between agents. Secondly, to address the difficulties that agents with different dimensions cannot communicate in fully heterogeneous stochastic MASs, a virtual state space is designed. According to the above framework, novel PETICs with/without actuation delays are presented to achieve the mean-square exponential consensus of fully heterogeneous stochastic MASs. Finally, the effectiveness of the proposed methods is verified through a numerical simulation of unmanned aerial vehicles and unmanned ground vehicles.

Periodic event-triggered impulsive control for fully heterogeneous stochastic multi-agent systems with a time-varying topology

TL;DR

This work addresses consensus in fully heterogeneous stochastic multi-agent systems with a time-varying topology by introducing a virtual state space to equalize agent dimensions and an energy-adaptive topology to modulate information flow. It develops periodic event-triggered impulsive controls (PETIC) with and without actuation delays, proving mean-square exponential convergence under specific conditions. The approach substantially reduces communication load while maintaining stability, demonstrated via UAV/UGV simulations with stochastic disturbances. Overall, the paper advances practical coordination for heterogeneous agents in energy-constrained, dynamic environments by combining topology adaptation, virtual-state reasoning, and PETIC to achieve robust consensus.

Abstract

In this paper, we focus on a periodic event-triggered impulsive control (PETIC) for fully heterogeneous stochastic multi-agent systems (MASs) with a time-varying topology. Firstly, a novel time-varying topology is established by incorporating the energy consumption of each agent. This topology enables active adjustment of the information interaction intensity between agents. Secondly, to address the difficulties that agents with different dimensions cannot communicate in fully heterogeneous stochastic MASs, a virtual state space is designed. According to the above framework, novel PETICs with/without actuation delays are presented to achieve the mean-square exponential consensus of fully heterogeneous stochastic MASs. Finally, the effectiveness of the proposed methods is verified through a numerical simulation of unmanned aerial vehicles and unmanned ground vehicles.
Paper Structure (11 sections, 37 equations, 8 figures)

This paper contains 11 sections, 37 equations, 8 figures.

Table of Contents

  1. Introduction
  2. Problem formulation
  3. Notations
  4. Time-varying Graph Theory
  5. A fully heterogeneous stochastic MAS
  6. Virtual state space
  7. Main results
  8. PETIC
  9. PETIC with actuation delay
  10. Numerical simulation
  11. Conclusions and future research prospects

Figures (8)

  • Figure 1: Configuration of a stochastic MAS with time-varying topology.
  • Figure 2: UAVs-UGVs system.
  • Figure 3: Position errors without control.
  • Figure 4: Velocity errors without control.
  • Figure 5: Simulation results of UAVs and UGVs under PETIC (\ref{['00']}) without actuation delays.
  • ...and 3 more figures

Theorems & Definitions (15)

  • Remark 1
  • Remark 2
  • Remark 3
  • Remark 4
  • Remark 5
  • Remark 6
  • Remark 7
  • Remark 8
  • Remark 9
  • Remark 10
  • ...and 5 more