Robust consensus method based on LPV multi-agent system

A multi-agent system and consensus technology, applied in general control systems, control/regulation systems, instruments, etc., can solve problems such as external interference of the system, achieve the effect of ensuring robust consensus and eliminating the dependence of algebraic connectivity

Inactive Publication Date: 2020-10-30
NANJING UNIV OF POSTS & TELECOMM
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AI Technical Summary

Problems solved by technology

So far, the consensus of various multi-agent systems has been extensively studied, but the multi-agent systems in most researches have the following disadvantages: there are various external disturbances in the system, and the external disturbances need to satisfy the linear parameter time-varying; An agent needs to implement multiple conditions to achieve consistency

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  • Robust consensus method based on LPV multi-agent system
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Embodiment Construction

[0059] The robust consensus method based on the LPV multi-agent system of the present invention, the process is as follows figure 1 As shown, the steps are as follows:

[0060] Step (1) Establish an uncertain linear LPV multi-agent system composed of N vertices, the mathematical expression of the system is:

[0061]

[0062] where A and B are constant matrices, satisfying x i and u i are the state of node i and the state of control input u respectively, satisfying ΔA is a real matrix function, satisfying: ‖ΔA‖≤d, d is a constant greater than 0; the system expression (1) satisfies (A, B) is stable.

[0063] Step (2) introduces a new upper bound of the P matrix in the continuous Riccati equation in the LPV multi-agent system;

[0064] Assuming that the constant β>0 satisfies A+A T T , when (A,B) is stable, any constant ε>0 satisfies the following continuous algebraic Riccati differential equation

[0065] A T P+PA-PBB T P=-εI N (2)

[0066] There is a unique posit...

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Abstract

The invention discloses a robust consensus method based on an LPV multi-agent system. The method comprises the following steps of establishing an uncertain linear LPV multi-agent system, introducing anew upper bound of a P matrix in a continuous Riccati equation into the system, applying a static protocol controller to the multi-agent system to obtain a multi-agent robust model, applying an edge-based adaptive strategy to the system to obtain an adaptive model, and applying a node-based adaptive strategy to the system to obtain an adaptive model. According to the method, a time-varying linearparameter is introduced into a multi-agent system to serve as external disturbance, and a new upper bound of a P matrix in a continuous algebra Riccati equation is utilized to obtain a sufficient condition, related to algebra connectivity, of the system; and an edge-based adaptive strategy and a node-based adaptive strategy are introduced, so that the multi-agent system can reach a consensus moreeasily.

Description

technical field [0001] The invention relates to the field of multi-agent formation control, in particular to a robust consensus method based on an LPV multi-agent system. Background technique [0002] In nature, people often see the flocking behavior of some organisms, such as flocks of birds that constantly change their flight shapes, colonies of ants that can drag objects many times larger than their own weight, swarms of fish swimming in groups in the ocean, etc. They gather together due to the nature of swarms. Through the study of these swarm behaviors, it is found that these creatures with simple structures present complex and efficient group behaviors through the ever-changing information exchange between individuals. This discovery inspired scholars to conduct in-depth research on the coordinated control of multi-agent systems. With the rapid development of communication technology and networks, artificial intelligence has received more and more attention. The coordi...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G05B13/04
CPCG05B13/042
Inventor 方荣肖敏王晓玲
Owner NANJING UNIV OF POSTS & TELECOMM
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