Sample-based Dynamic Event-triggered Algorithm for Optimization Problem of Multi-agent Systems

The convex optimization problem of multi-agent systems is investigated. In order to deduce the communication burden of the system and simplify the implementation of the algorithm on the digital controllers, a sample-based event-triggered optimization algorithm is proposed and a novel dynamic event-t...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:International journal of control, automation, and systems Jg. 20; H. 8; S. 2492 - 2502
1. Verfasser: Zhao, Zhongyuan
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Bucheon / Seoul Institute of Control, Robotics and Systems and The Korean Institute of Electrical Engineers 01.08.2022
Springer Nature B.V
제어·로봇·시스템학회
Schlagworte:
Algorithms
Communications systems
Computational geometry
Control
Control Theory and Applications
Convexity
Engineering
Mechatronics
Multiagent systems
Optimization
Robotics
제어계측공학
optimization problem
dynamic event-triggered
zero-gradient-sum algorithm
Consensus
ISSN:1598-6446, 2005-4092
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:The convex optimization problem of multi-agent systems is investigated. In order to deduce the communication burden of the system and simplify the implementation of the algorithm on the digital controllers, a sample-based event-triggered optimization algorithm is proposed and a novel dynamic event-trigged condition is designed. The global optimal solution can be obtained exponentially. The event-triggered time intervals are significantly enlarged by dynamic event-triggered condition. Moreover, Zeno behavior is excluded due to sampling control mechanism in our scheme. Two numerical cases are presented to validate the relevant results.
Bibliographie:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
http://link.springer.com/article/10.1007/s12555-021-0157-2
ISSN:1598-6446
2005-4092
DOI:10.1007/s12555-021-0157-2