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A distributed optimization method for directed multi-agent networks based on rough information

A multi-agent, optimization method technology, applied in the transmission system, electrical components, etc., can solve the problem of high cost of node storage space, and achieve the effect of expanding the actual application scene, enhancing the feasibility, and strong practicability

Active Publication Date: 2022-04-22
东北大学秦皇岛分校
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  • Description
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  • Application Information

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Problems solved by technology

[0007] Aiming at the deficiencies of the prior art, the present invention provides a distributed optimization method for a directed multi-agent network based on rough information, so that it no longer needs the out-degree information of the nodes, and the algorithm does not require the network Laplacian matrix Estimate the left eigenvector of the node, thus avoiding the problem of excessive cost of node storage space

Method used

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  • A distributed optimization method for directed multi-agent networks based on rough information
  • A distributed optimization method for directed multi-agent networks based on rough information
  • A distributed optimization method for directed multi-agent networks based on rough information

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Embodiment Construction

[0038] The specific embodiments of the present invention will be described in detail below in conjunction with the accompanying drawings.

[0039] A distributed optimization method for directed multi-agent networks based on rough information, such as figure 1 shown, including the following steps:

[0040] Step 1: Establish a distributed optimization model for agents in a multi-agent network, specifically to solve the convex function f i The constraints of (x) and are minimized, and the properties of the convex function are set;

[0041] The constrained minimization refers to finding the convex function f when the state value x is constrained by the range i (x) and the minimum value;

[0042] The optimization model is represented by the following formula:

[0043]

[0044] where f i (x) is a strong convex function, α is its strong convex coefficient, and the constraint set is a non-empty, closed convex set, n is the number of nodes, R is the field of real numbers, and...

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Abstract

The invention provides a distributed optimization method of directed multi-agent network based on rough information, which relates to the field of control and information technology. The present invention only considers rough information between adjacent nodes, and each node only needs to know the state information of in-degree neighbors, which minimizes necessary conditions and enhances the feasibility of the algorithm in practical applications. In the case of only obtaining the rough state information between the agent and its in-degree neighbors, the algorithm can still fuse the information of adjacent nodes well, so that the state convergence of the nodes tends to be consistent, and finally converges to an approximate optimal solution.

Description

technical field [0001] The invention relates to the field of control and information technology, in particular to a distributed optimization method of directed multi-agent network based on rough information. Background technique [0002] A multi-agent network refers to a network composed of multiple agents, each of which is a physical or abstract entity with three basic characteristics: sensing the environment, computing / processing information, and communicating with adjacent agents. In practical applications, the agents in the multi-agent network can be a set of software, or hardware such as drones and robots. According to whether global information is required, multi-agent network optimization problems can be divided into three methods: centralized, decentralized and distributed. The distributed optimization problem refers to the design of an optimization strategy for processing the global objective function by exchanging information with adjacent agents when each agent o...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): H04L41/12H04L67/12
CPCH04L41/12H04L67/12
Inventor 陈飞金瑾项林英魏永涛孙文义
Owner 东北大学秦皇岛分校