Skip to Main content Skip to Navigation
Journal articles

Mean Square Consensus of Double-Integrator Multi-Agent Systems under Intermittent Control: A Stochastic Time Scale Approach

Abstract : We consider the leader–follower consensus problem for a multi-agent system where information is exchanged only on a non-uniform discrete stochastic time domain. For a second-order multi-agent system subject to intermittent information exchange, we model the tracking error dynamics as a μ−varying linear system on a discrete stochastic time scale, where μ is the graininess operator. Based on a Lyapunov operator and a positive perturbation operator on the space of symmetric matrices, we derive necessary and sufficient conditions to design a decentralized consensus protocol. This protocol allows us to cast the mean-square exponential consensus problem within the framework of dynamic equations on stochastic time scales. We establish some theoretical results which allow for the computation of the control gain matrix which guarantees the mean-square exponential stability with a given decay rate for the error dynamics. To show the effectiveness of the theoretical results, some simulation and experimental results on multi-robot systems have been performed.
Document type :
Journal articles
Complete list of metadata

https://hal-uphf.archives-ouvertes.fr/hal-03405351
Contributor : Frédéric Pruvost Connect in order to contact the contributor
Submitted on : Wednesday, October 27, 2021 - 11:07:03 AM
Last modification on : Thursday, May 19, 2022 - 9:21:15 AM

Identifiers

Collections

Citation

Dylan Poulsen, Michael Defoort, Mohamed Djemai. Mean Square Consensus of Double-Integrator Multi-Agent Systems under Intermittent Control: A Stochastic Time Scale Approach. Journal of The Franklin Institute, Elsevier, 2019, 356 (16), pp.9076-9094. ⟨10.1016/j.jfranklin.2019.07.011⟩. ⟨hal-03405351⟩

Share

Metrics

Record views

5