.png){kind=icon}
Return
Event-Triggered Distributed Average Tracking Control for Lipschitz-Type Nonlinear Multiagent Systems
.png){kind=icon}
PRE
AI
DOI：10.1109/TCYB.2022.3159250.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
This article investigates the event-triggered distributed average tracking (ETDAT) control problems for the Lipschitz-type nonlinear multiagent systems with bounded time-varying reference signals. By using the state-dependent gain design approach and event-triggered mechanism, two types of ETDAT algorithms called: 1) static and 2) adaptive-gain ETDAT algorithms are developed. It is the first time to introduce the event-triggered strategy into DAT control algorithms and investigate the ETDAT problem for multiagent systems with Lipschitz nonlinearities, which is more practical in real physical systems and can better meet the needs of practical engineering applications. Besides, the adaptive-gain ETDAT algorithms do not need any global information of the network topology and are fully distributed. Finally, a simulation example of the Watts-Strogatz small-world network is presented to illustrate the effectiveness of the adaptive-gain ETDAT algorithms.
Keywords:
Multi-agent systems
Eigenvalues and eigenfunctions
Nonlinear dynamical systems
Heuristic algorithms
Trajectory
Topology
Symbols
Adaptive gain technique
event-triggered distributed average tracking (ETDAT)
Lipschitz nonlinearities
multiagent systems
state-dependent gain
Journal
IF:
10.5
Papers:
1.1W
Citations:
5.0W
Organization
View more organizations
Cited Papers
ShareSaveDecentralized event-triggered consensus for linear multi-agent systems under general directed graphs.png)
AUTOMATICA
OAAI
AUTOMATICAIF5.9
OAAIShareSaveShareSaveShareSaveDistributed finite-time tracking of multiple non-identical second-order nonlinear systems with settling time estimationAUTOMATICA
AUTOMATICAIF5.9
PREAI
ShareSave View more