An Efficient Distributed Parallel Algorithm for Optimal Consensus of Multiagent Systems

A parallel algorithm is presented in this article to efficiently solve the optimal consensus problem of multiagent systems. By utilizing a Jacobi-type proximal alternating direction multiplier framework, the optimization process is divided into two independent subproblems that can be solved in paral...

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Bibliographic Details
Published in:IEEE transactions on control of network systems Vol. 11; no. 3; pp. 1440 - 1451
Main Authors: Bai, Nan, Wang, Qishao, Duan, Zhisheng
Format: Journal Article
Language:English
Published: Piscataway IEEE 01.09.2024
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:
Algorithms
Convergence
Convex optimization
Convexity
Costs
distributed optimization
Jacobian matrices
Lagrange multiplier
Multi-agent systems
Multiagent systems
optimal consensus
Optimization
parallel algorithm
Parallel algorithms
Parameters
Protocols
ISSN:2325-5870, 2372-2533
Online Access:Get full text
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Summary:A parallel algorithm is presented in this article to efficiently solve the optimal consensus problem of multiagent systems. By utilizing a Jacobi-type proximal alternating direction multiplier framework, the optimization process is divided into two independent subproblems that can be solved in parallel to improve computational efficiency, followed by the Lagrangian multiplier update. The convergence analysis of the proposed algorithm is performed using the convex optimization theory, deriving the convergence conditions concerning the auxiliary parameters. Furthermore, the accelerated algorithm enjoys a convergence rate of <inline-formula><tex-math notation="LaTeX">\mathcal {O}(\frac{1}{t^{2}})</tex-math></inline-formula> by adjusting the auxiliary parameters adaptively. To leverage the strengths of the collaboration of multiagent systems, the distributed implementation of the proposed parallel algorithm is further developed, where each agent addresses its private subproblems only using its own and its neighbor's information. Numerical simulations demonstrate the effectiveness of the theoretical results.
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ISSN:2325-5870
2372-2533
DOI:10.1109/TCNS.2023.3338245