A fixed-time convergent algorithm for distributed convex optimization in multi-agent systems

This technical paper presents a distributed continuous-time algorithm to solve multi-agent optimization problem with the team objective being the sum of all local convex objective functions while subject to an equality constraint. The optimal solutions are achieved within fixed time which is indepen...

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Bibliographic Details
Published inAutomatica (Oxford) Vol. 95; pp. 539 - 543
Main Authors Chen, Gang, Li, Zhiyong
Format Journal Article
LanguageEnglish
Published Elsevier Ltd 01.09.2018
Subjects
Convex optimization
Distributed algorithm
Equality constraint
Fixed-time convergence
Multi-agent system
Multi-agent system
Fixed-time convergence
Convex optimization
Distributed algorithm
Equality constraint
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Summary:This technical paper presents a distributed continuous-time algorithm to solve multi-agent optimization problem with the team objective being the sum of all local convex objective functions while subject to an equality constraint. The optimal solutions are achieved within fixed time which is independent of the initial conditions of agents. This advantage makes it possible to off-line preassign the settling time according to task requirements. The fixed-time convergence for the proposed algorithm is rigorously proved with the aid of convex optimization and fixed-time Lyapunov theory. Finally, the algorithm is valuated via an example.
ISSN:0005-1098
1873-2836
DOI:10.1016/j.automatica.2018.05.032