Distributed Adaptive Optimization for Generalized Linear Multiagent Systems
Joint Authors
Mei, Xuehui
Jiang, Haijun
Liu, Shuxin
Zhang, Liwei
Source
Discrete Dynamics in Nature and Society
Issue
Vol. 2019, Issue 2019 (31 Dec. 2019), pp.1-10, 10 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2019-08-01
Country of Publication
Egypt
No. of Pages
10
Main Subjects
Abstract EN
In this paper, the edge-based and node-based adaptive algorithms are established, respectively, to solve the distribution convex optimization problem.
The algorithms are based on multiagent systems with general linear dynamics; each agent uses only local information and cooperatively reaches the minimizer.
Compared with existing results, a damping term in the adaptive law is introduced for the adaptive algorithms, which makes the algorithms more robust.
Under some sufficient conditions, all agents asymptotically converge to the consensus value which minimizes the cost function.
An example is provided for the effectiveness of the proposed algorithms.
American Psychological Association (APA)
Liu, Shuxin& Jiang, Haijun& Zhang, Liwei& Mei, Xuehui. 2019. Distributed Adaptive Optimization for Generalized Linear Multiagent Systems. Discrete Dynamics in Nature and Society،Vol. 2019, no. 2019, pp.1-10.
https://search.emarefa.net/detail/BIM-1146650
Modern Language Association (MLA)
Liu, Shuxin…[et al.]. Distributed Adaptive Optimization for Generalized Linear Multiagent Systems. Discrete Dynamics in Nature and Society No. 2019 (2019), pp.1-10.
https://search.emarefa.net/detail/BIM-1146650
American Medical Association (AMA)
Liu, Shuxin& Jiang, Haijun& Zhang, Liwei& Mei, Xuehui. Distributed Adaptive Optimization for Generalized Linear Multiagent Systems. Discrete Dynamics in Nature and Society. 2019. Vol. 2019, no. 2019, pp.1-10.
https://search.emarefa.net/detail/BIM-1146650
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1146650