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Designing Zero-Gradient-Sum Protocols for Finite-Time Distributed Optimization Problem
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DOI：10.1109/TSMC.2021.3098641.png)
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Abstract
En 中文
In this article, the distributed finite-time and fixed-time optimization problems are investigated by adopting the zero-gradient-sum (ZGS) framework in multiagent systems. Specifically, when the local convex functions are nonquadratic, a basic optimization protocol is proposed to obtain a finite-time convergence, such that the networked system can cooperatively seek the optimal solution of the global objective, the sum of local objective, in a limited time. By utilizing the property of quadratic functions, a reduced algorithm can remove the dependence of initial conditions in the estimation of the upper bound of settling time and achieve a fixed-time result. Besides, the problem with time-varying topologies is studied by introducing a modified algorithm with an artificial potential function to preserve the network connectivity. Finally, the validity of the protocols is demonstrated via some example simulations.
Keywords:
Optimization
Protocols
Convergence
Multi-agent systems
Convex functions
Topology
Upper bound
Convex optimization
distributed protocol
finite-time stability
multiagent system
Journal
IF:
10.5
Papers:
1.1W
Citations:
5.0W