Dynamic Event-Triggered and Self-Triggered Control for Multi-agent Systems

We propose two novel dynamic event-triggered control laws to solve the average consensus problem for first-order continuous-time multiagent systems over undirected graphs. Compared with the most existing triggering laws, the proposed laws involve internal dynamic variables, which play an essential r...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:IEEE transactions on automatic control Jg. 64; H. 8; S. 3300 - 3307
Hauptverfasser: Yi, Xinlei, Liu, Kun, Dimarogonas, Dimos V., Johansson, Karl H.
Format: Journal Article
Sprache:Englisch
Veröffentlicht: New York IEEE 01.08.2019
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:
Algorithms
Computer simulation
Consensus
Control systems
Control theory
dynamic event-triggered control
Heuristic algorithms
Multi-agent systems
Multiagent systems
Protocols
self-triggered control
Sensors
Symmetric matrices
Vehicle dynamics
ISSN:0018-9286, 1558-2523, 1558-2523
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:We propose two novel dynamic event-triggered control laws to solve the average consensus problem for first-order continuous-time multiagent systems over undirected graphs. Compared with the most existing triggering laws, the proposed laws involve internal dynamic variables, which play an essential role in guaranteeing that the triggering time sequence does not exhibit Zeno behavior. Moreover, some existing triggering laws are special cases of ours. For the proposed self-triggered algorithm, continuous agent listening is avoided as each agent predicts its next triggering time and broadcasts it to its neighbors at the current triggering time. Thus, each agent only needs to sense and broadcast at its triggering times, and to listen to and receive incoming information from its neighbors at their triggering times. It is proved that the proposed triggering laws make the state of each agent converge exponentially to the average of the agents' initial states if and only if the underlying graph is connected. Numerical simulations are provided to illustrate the effectiveness of the theoretical results.
Bibliographie:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:0018-9286
1558-2523
1558-2523
DOI:10.1109/TAC.2018.2874703