Journal ArticleDOI
Regularized Primal–Dual Subgradient Method for Distributed Constrained Optimization
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This paper proposes a consensus-based distributed regularized primal-dual subgradient method for distributed constrained optimization, where the objective function is the sum of local convex cost functions of distributed nodes in a network, subject to a global inequality constraint.Abstract:
In this paper, we study the distributed constrained optimization problem where the objective function is the sum of local convex cost functions of distributed nodes in a network, subject to a global inequality constraint. To solve this problem, we propose a consensus-based distributed regularized primal–dual subgradient method. In contrast to the existing methods, most of which require projecting the estimates onto the constraint set at every iteration, only one projection at the last iteration is needed for our proposed method. We establish the convergence of the method by showing that it achieves an $ {\mathcal {O}} {(} {K}^{ {-1/4}} {)}$ convergence rate for general distributed constrained optimization, where ${K}$ is the iteration counter. Finally, a numerical example is provided to validate the convergence of the propose method.read more
Citations
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A survey of distributed optimization
Tao Yang,Xinlei Yi,Junfeng Wu,Ye Yuan,Di Wu,Ziyang Meng,Yiguang Hong,Hong Wang,Zongli Lin,Karl Henrik Johansson +9 more
TL;DR: This survey paper aims to offer a detailed overview of existing distributed optimization algorithms and their applications in power systems, and focuses on the application of distributed optimization in the optimal coordination of distributed energy resources.
Journal ArticleDOI
Pulse-Modulated Intermittent Control in Consensus of Multiagent Systems
TL;DR: A control framework, called pulse-modulated intermittent control, is proposed, which unifies impulsive control and sampled control and a lower bound of the asymptotic convergence factor is derived.
Journal ArticleDOI
Distributed Optimization for Linear Multiagent Systems: Edge- and Node-Based Adaptive Designs
TL;DR: This paper studies the distributed optimization problem for continuous-time multiagent systems with general linear dynamics to cooperatively optimize a team performance function formed by a sum of convex local objective functions.
Journal ArticleDOI
Distributed Optimal Consensus Over Resource Allocation Network and Its Application to Dynamical Economic Dispatch
TL;DR: A novel distributed primal–dual dynamical multiagent system is designed in a smart grid scenario to seek the saddle point of dynamical economic dispatch, which coincides with the optimal solution.
Journal ArticleDOI
Distributed Continuous-Time Algorithms for Resource Allocation Problems Over Weight-Balanced Digraphs
TL;DR: A distributed continuous-time algorithm is developed by virtue of differentiated projection operations and differential inclusions, and its convergence to the optimal solution is proved via the set-valued LaSalle invariance principle.
References
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Consensus problems in networks of agents with switching topology and time-delays
TL;DR: A distinctive feature of this work is to address consensus problems for networks with directed information flow by establishing a direct connection between the algebraic connectivity of the network and the performance of a linear consensus protocol.
Journal ArticleDOI
Coordination of groups of mobile autonomous agents using nearest neighbor rules
Ali Jadbabaie,Jie Lin,A.S. Morse +2 more
TL;DR: A theoretical explanation for the observed behavior of the Vicsek model, which proves to be a graphic example of a switched linear system which is stable, but for which there does not exist a common quadratic Lyapunov function.
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Consensus seeking in multiagent systems under dynamically changing interaction topologies
Wei Ren,Randal W. Beard +1 more
TL;DR: It is shown that information consensus under dynamically changing interaction topologies can be achieved asymptotically if the union of the directed interaction graphs have a spanning tree frequently enough as the system evolves.
Journal ArticleDOI
Distributed Subgradient Methods for Multi-Agent Optimization
Angelia Nedic,Asuman Ozdaglar +1 more
TL;DR: The authors' convergence rate results explicitly characterize the tradeoff between a desired accuracy of the generated approximate optimal solutions and the number of iterations needed to achieve the accuracy.
Journal ArticleDOI
Fast linear iterations for distributed averaging
Lin Xiao,Stephen Boyd +1 more
TL;DR: This work considers the problem of finding a linear iteration that yields distributed averaging consensus over a network, i.e., that asymptotically computes the average of some initial values given at the nodes, and gives several extensions and variations on the basic problem.
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