.png){kind=icon}
Return
Model Reference Adaptive Stabilizing Control With Application to Leaderless Consensus
.png){kind=icon}
OA
AI
DOI：10.1109/TAC.2023.3313642.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
This article describes an extension of the well-known model reference adaptive control (MRAC) approach. The extension relies on explicitly involving the tracking error in the feedback control law: it is shown that including this term along with its appropriate extra adaptive gain allows one to handle possibly unstable reference dynamics. Owing to its stabilizing nature, the proposed framework is referred to as model reference adaptive stabilizing control. Such an extension turns out to be particularly useful in leaderless consensus of heterogeneous uncertain agents, since the literature has discussed that leaderless adaptation may not avoid unstable closed-loop dynamics. In such consensus setting, the framework, referred to as model reference adaptive stabilizing consensus, generalizes the existing MRAC-based consensus schemes and can achieve consensus when state-of-the-art MRAC-based schemes may fail.
Keywords:
Adaptation models
Standards
Mathematical models
Observers
Adaptive control
Target tracking
Multi-agent systems
Adaptive stabilization
consensus
directed spanning tree
model reference adaptive control (MRAC)
multiagent systems
Journal
IF:
7
Papers:
1.3W
Citations:
6.7W
Organization
Cited Papers
.png){kind=icon}
ShareSaveOutput Synchronization of Unknown Heterogeneous Agents via Distributed Model Reference Adaptation
OAAI
OAAIShareSaveShareSave
View more