.png){kind=icon}
.png){kind=icon}
Return
Distributed finite-time optimization algorithms for multi-agent systems under directed graphs
.png){kind=icon}
PRE
AI
DOI：10.1002/rnc.6699.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
Existing distributed finite-time optimization algorithms for continuous-time multi-agent systems require either undirected graphs or weight balanced digraphs, and distributed finite-time optimization problems for weight unbalanced digraphs are still great challenging. Thus, the distributed finite-time optimization problems for continuous-time multi-agent systems with strongly convex local cost functions are investigated under directed graphs in this article. First, a distributed finite-time gradient estimator is constructed by using non-smooth analysis and algebraic graph theory, then distributed finite-time optimization algorithms and piecewise distributed finite-time optimization algorithms are proposed based on the designed gradient estimator. The new proposed distributed finite-time optimization algorithms which only require strongly connected graphs relax the balanced requirement. Furthermore, the communication bandwidth of systems could be saved by deploying the proposed piecewise distributed finite-time optimization algorithms since the information exchange in the optimization process is reduced. Finally, simulation examples are given to verify the effectiveness of proposed distributed optimization algorithms.
Keywords:
convex functions
cooperative control
directed graphs
distributed optimization
finite-time optimization
multi-agent systems
Journal
IF:
3.2
Papers:
6.9K
Citations:
1.4W