Nonsmooth Resource Allocation of Multiagent Systems With Disturbances: A Proximal Approach

This article aims to solve the nonsmooth resource allocation problem in the presence of a global network resource constraint and local set constraints in the framework of multiagent system optimization. It is assumed that multiagent systems are subject to some external disturbances, and the control...

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Veröffentlicht in:IEEE transactions on control of network systems Jg. 8; H. 3; S. 1454 - 1464
Hauptverfasser: Zhu, Yanan, Wen, Guanghui, Yu, Wenwu, Yu, Xinghuo
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Piscataway IEEE 01.09.2021
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:
Algorithms
Communication
Computational geometry
Control systems
Convex functions
Convexity
Disturbance rejection
Disturbances
event-based comm- unication
Heuristic algorithms
Mathematical models
Multi-agent systems
Multiagent systems
Optimization
proximal algorithm
Resource allocation
Resource management
Symmetric matrices
ISSN:2325-5870, 2372-2533
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Zusammenfassung:This article aims to solve the nonsmooth resource allocation problem in the presence of a global network resource constraint and local set constraints in the framework of multiagent system optimization. It is assumed that multiagent systems are subject to some external disturbances, and the control inputs of the agents satisfy Lispchitz continuity. These two distinguished features render the existing distributed optimization algorithms, especially the subgradient-based algorithms inapplicable due to the employment of discontinuity of subgradients. To solve such a challenging resource allocation problem, a new kind of continuous-time proximal algorithm is designed with the aid of convex optimization theory and the internal-model technique. The proximal algorithm is further augmented by introducing an event-based communication scheme such that the continuous-time communication among the agents is avoided successfully. The theoretical analysis shows that the multiagent systems under the proposed algorithms can converge to the optimal solution of the considered problem, while the external disturbances are rejected. Besides, the Zeno behavior can be excluded for the proximal algorithm with event-based communication. Finally, the numerical simulations are given to verify the established theoretical results.
Bibliographie:ObjectType-Article-1
SourceType-Scholarly Journals-1
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ISSN:2325-5870
2372-2533
DOI:10.1109/TCNS.2021.3068349