Method for controlling distributed average tracking of linear differential inclusion multi-agent systems

A multi-agent system, distributed averaging technology, applied in the field of multi-agent systems
CN105634828AInactive Publication Date: 2016-06-01XIAMEN UNIV
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Patent Information

Authority / Receiving Office
CN ยท China
Current Assignee / Owner
XIAMEN UNIV
Publication Date
2016-06-01
Estimated Expiration
Not applicable ยท inactive patent

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Abstract

The invention relates to a method for controlling distributed average tracking of linear differential inclusion multi-agent systems, relating to multi-agent systems. The method comprises the following steps of: constructing a network structure topological graph of multiple agents to obtain an adjacent matrix, an associated matrix and a Laplacian matrix of the graph; setting an initial state and an initial reference signal of each node; constructing a linear differential inclusion system, and setting a system matrix to obtain a system parameter; setting a communication manner, such that each node is only communicated with a neighbour node, operating a distributed average tracking algorithm, and adjusting the state of each node; and designing a control law according to feedback information and the system parameter, adjusting the node state to achieve consistency, and tracking an average value of the reference signal. Requirements on the network structure are low; only when a network is connected, all node states tend to be uniform; furthermore, the average value of the reference signal is tracked; in the whole calculation process, each node only uses information of the neighbour node; the calculation amount is low; and the operation efficiency of the algorithm is increased.
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Description

technical field

[0001] The invention relates to a multi-agent system, in particular to a control method for linear differential including distributed average tracking of a multi-agent system. Background technique

[0002] A multi-agent system is a collection of multiple coupled agent systems. Each agent system has a certain degree of autonomy and can communicate with other agents by sensing the surrounding environment. With the development in recent years, distributed cooperative control of multi-agent systems has become a hotspot in the field of control research. Compared with centralized control, distributed control has the advantages of low cost, high reliability, high flexibility, and high scalability, and has a wide range of engineering background and application prospects. Distributed convergence is a central problem in the research of multi-agent systems, and its goal is to design a distributed controller to make the states of all agents finally reach the same. The ...

Claims

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