Paper Info
Title
Distributed Continuous-Time and Discrete-Time Optimization With Nonuniform Unbounded Convex Constraint Sets and Nonuniform Stepsizes
Abstract
This paper is devoted to distributed continuous-time and discrete-time optimization problems with nonuniform convex constraint sets and nonuniform stepsizes for general differentiable convex objective functions. The communication graphs are not required to be strongly connected at any time, the gradients of the local objective functions are not required to be bounded when their independent variables tend to infinity, and the constraint sets are not required to be bounded. For continuous-time multiagent systems, a distributed continuous algorithm is first introduced where the stepsizes and the convex constraint sets are both nonuniform. It is shown that all agents reach a consensus while minimizing the team objective function even when the constraint sets are unbounded. After that, the obtained results are extended to discrete-time multiagent systems and then the case where each agent remains in a corresponding convex constraint set is studied. To ensure all agents to remain in a bounded region, a switching mechanism is introduced in the algorithms. It is shown that the distributed optimization problems can be solved, even though the discretization of the algorithms might deviate the convergence of the agents from the minimum of the objective functions.
Year
DOI
Venue
2019
10.1109/TAC.2019.2910946
IEEE Transactions on Automatic Control
Keywords
Field
DocType
Distributed optimization,nonuniform convex constraint sets,nonuniform step-sizes
Convergence (routing),Discretization,Mathematical optimization,Regular polygon,Differentiable function,Discrete time and continuous time,Strongly connected component,Optimization problem,Mathematics,Bounded function
Journal
Volume
Issue
ISSN
64
12
0018-9286
Citations 
PageRank 
References 
5
0.41
30
Authors
4
Name
Order
Citations
PageRank
Peng Lin11206.31
Wei Ren25238250.63
Chunhua Yang343571.63
Weihua Gui457790.82