Distributed Optimization Algorithm for Discrete-Time Heterogeneous Multi-Agent Systems With Nonuniform Stepsizes

This paper is devoted to the distributed optimization problem of heterogeneous multi-agent systems, where the communication topology is jointly strongly connected and the dynamics of each agent is the first-order or second-order integrator. A new distributed algorithm is first designed for each agen...

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Bibliographic Details
Published inIEEE access Vol. 7; pp. 87303 - 87312
Main Authors Mo, Lipo, Li, Jingyi, Huang, Jian
Format Journal Article
LanguageEnglish
Published Piscataway IEEE 2019
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects
Algorithms
Discrete time systems
Distributed algorithms
Distributed optimization
Feedback control
heterogeneous
Laplace equations
Linear programming
Multi-agent systems
Multiagent systems
nonuniform stepsizes
Optimization
Topology
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Summary:This paper is devoted to the distributed optimization problem of heterogeneous multi-agent systems, where the communication topology is jointly strongly connected and the dynamics of each agent is the first-order or second-order integrator. A new distributed algorithm is first designed for each agent based on the local objective function and the local neighbors' information that each agent can access. By a model transformation, the original closed-loop system is converted into a time-varying system and the system matrix of which is a stochastic matrix at any time. Then, by the properties of the stochastic matrix, it is proven that all agents' position states can converge to the optimal solution of a team objective function provided the union communication topology is strongly connected. Finally, the simulation results are provided to verify the effectiveness of the distributed algorithm proposed in this paper.
ISSN:2169-3536
2169-3536
DOI:10.1109/ACCESS.2019.2925414