Distributed dynamic event-triggered control for multi-agent systems

Xinlei Yi; Kun Liu; Dimos V. Dimarogonas; Karl H. Johansson

doi:10.1109/CDC.2017.8264666

Distributed dynamic event-triggered control for multi-agent systems

Xinlei Yi^*, Kun Liu, Dimos V. Dimarogonas, Karl H. Johansson

^*Corresponding author for this work

School of Automation

KTH Royal Institute of Technology

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

60 Citations (Scopus)

Abstract

We propose two distributed dynamic triggering laws to solve the consensus problem for multi-agent systems with event-triggered consensus protocol. Compared with existing triggering laws, the proposed triggering laws involve internal dynamic variables which play an essential role to guarantee that the triggering time sequence does not exhibit Zeno behavior. Some existing triggering laws are special cases of our dynamic triggering laws. Under the condition that the underlying graph is undirected and connected, it is proven that the proposed dynamic triggering laws together with the event-triggered consensus protocol make the state of each agent converges exponentially to the average of the agents' initial states. Numerical simulations illustrate the effectiveness of the theoretical results.

Original language	English
Title of host publication	2017 IEEE 56th Annual Conference on Decision and Control, CDC 2017
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	6683-6688
Number of pages	6
ISBN (Electronic)	9781509028733
DOIs	https://doi.org/10.1109/CDC.2017.8264666
Publication status	Published - 28 Jun 2017
Event	56th IEEE Annual Conference on Decision and Control, CDC 2017 - Melbourne, Australia Duration: 12 Dec 2017 → 15 Dec 2017

Publication series

Name	2017 IEEE 56th Annual Conference on Decision and Control, CDC 2017
Volume	2018-January

Conference

Conference	56th IEEE Annual Conference on Decision and Control, CDC 2017
Country/Territory	Australia
City	Melbourne
Period	12/12/17 → 15/12/17

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10.1109/CDC.2017.8264666

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Yi, X., Liu, K., Dimarogonas, D. V., & Johansson, K. H. (2017). Distributed dynamic event-triggered control for multi-agent systems. In 2017 IEEE 56th Annual Conference on Decision and Control, CDC 2017 (pp. 6683-6688). (2017 IEEE 56th Annual Conference on Decision and Control, CDC 2017; Vol. 2018-January). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CDC.2017.8264666

@inproceedings{2faf927d00304ec18787308cd09d5c4f,

title = "Distributed dynamic event-triggered control for multi-agent systems",

abstract = "We propose two distributed dynamic triggering laws to solve the consensus problem for multi-agent systems with event-triggered consensus protocol. Compared with existing triggering laws, the proposed triggering laws involve internal dynamic variables which play an essential role to guarantee that the triggering time sequence does not exhibit Zeno behavior. Some existing triggering laws are special cases of our dynamic triggering laws. Under the condition that the underlying graph is undirected and connected, it is proven that the proposed dynamic triggering laws together with the event-triggered consensus protocol make the state of each agent converges exponentially to the average of the agents' initial states. Numerical simulations illustrate the effectiveness of the theoretical results.",

author = "Xinlei Yi and Kun Liu and Dimarogonas, {Dimos V.} and Johansson, {Karl H.}",

note = "Publisher Copyright: {\textcopyright} 2017 IEEE.; 56th IEEE Annual Conference on Decision and Control, CDC 2017 ; Conference date: 12-12-2017 Through 15-12-2017",

year = "2017",

month = jun,

day = "28",

doi = "10.1109/CDC.2017.8264666",

language = "English",

series = "2017 IEEE 56th Annual Conference on Decision and Control, CDC 2017",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

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Yi, X, Liu, K, Dimarogonas, DV & Johansson, KH 2017, Distributed dynamic event-triggered control for multi-agent systems. in 2017 IEEE 56th Annual Conference on Decision and Control, CDC 2017. 2017 IEEE 56th Annual Conference on Decision and Control, CDC 2017, vol. 2018-January, Institute of Electrical and Electronics Engineers Inc., pp. 6683-6688, 56th IEEE Annual Conference on Decision and Control, CDC 2017, Melbourne, Australia, 12/12/17. https://doi.org/10.1109/CDC.2017.8264666

Distributed dynamic event-triggered control for multi-agent systems. / Yi, Xinlei; Liu, Kun; Dimarogonas, Dimos V. et al.
2017 IEEE 56th Annual Conference on Decision and Control, CDC 2017. Institute of Electrical and Electronics Engineers Inc., 2017. p. 6683-6688 (2017 IEEE 56th Annual Conference on Decision and Control, CDC 2017; Vol. 2018-January).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Johansson, Karl H.

PY - 2017/6/28

Y1 - 2017/6/28

N2 - We propose two distributed dynamic triggering laws to solve the consensus problem for multi-agent systems with event-triggered consensus protocol. Compared with existing triggering laws, the proposed triggering laws involve internal dynamic variables which play an essential role to guarantee that the triggering time sequence does not exhibit Zeno behavior. Some existing triggering laws are special cases of our dynamic triggering laws. Under the condition that the underlying graph is undirected and connected, it is proven that the proposed dynamic triggering laws together with the event-triggered consensus protocol make the state of each agent converges exponentially to the average of the agents' initial states. Numerical simulations illustrate the effectiveness of the theoretical results.

AB - We propose two distributed dynamic triggering laws to solve the consensus problem for multi-agent systems with event-triggered consensus protocol. Compared with existing triggering laws, the proposed triggering laws involve internal dynamic variables which play an essential role to guarantee that the triggering time sequence does not exhibit Zeno behavior. Some existing triggering laws are special cases of our dynamic triggering laws. Under the condition that the underlying graph is undirected and connected, it is proven that the proposed dynamic triggering laws together with the event-triggered consensus protocol make the state of each agent converges exponentially to the average of the agents' initial states. Numerical simulations illustrate the effectiveness of the theoretical results.

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M3 - Conference contribution

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PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 56th IEEE Annual Conference on Decision and Control, CDC 2017

Y2 - 12 December 2017 through 15 December 2017

ER -

Distributed dynamic event-triggered control for multi-agent systems

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