.png){kind=icon}
Return
A Specified-Time Distributed Optimization Algorithm for Multiagent Systems With Time-Varying Constraints
.png){kind=icon}
PRE
AI
DOI：10.1109/TAC.2025.3616506.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
In this article, a class of distributed optimization problems for multiagent systems subject to time-varying coupling equality constraint is investigated. The global objective function is a sum of local convex objective functions and only local information is exchanged among the agents over a connected and undirected communication network. Based on convex optimization and Lyapunov stability theory, we show that the multiagent system in closed loop with the proposed distributed protocol is able to converge to the time-dependent unique optimum within a specified time. Remarkably, the convergence time is independent of the initial conditions and can be specified in advance making the proposed scheme suitable for application with strict requirements on the convergence. We validate through simulations the effectiveness of the theoretical results.
Keywords:
Distributed optimization
multiagent systems
specified-time convergence
time-varying equality constraint
Journal
IF:
7
Papers:
1.3W
Citations:
6.7W
Organization
View more organizations
Cited Papers
ShareSaveShareSave
A fixed-time convergent algorithm for distributed convex optimization in multi-agent systems.png)
AUTOMATICA
AUTOMATICAIF5.9
PREAI
ShareSaveShareSave
ShareSave View more